Search

To secure the sensitive information, EMRs usually should be encrypted before being stored on the cloud. However, the existing searchable encryption schemes that are used to encrypt the entire EMRs can hide the sensitive information, but results in the shared EMRs unable to be used by researchers. In addition, if the queried and extracted EMRs are incorrect, it will lead to misdiagnosis even endanger patients' life. In order to solve the above problems, we propose a verifiable keyword search scheme supporting sensitive information hiding for the cloud-based healthcare sharing system. The sensitive information is encrypted while other contents in EMR can be shared among users in this scheme. The doctors and researchers can quickly perform search operations based on keyword to extract the EMRs they requires. But the sensitive information is hidden for the researchers. Furthermore, the correctness of EMRs can be verified when they are extracted from the cloud.

The current rise of artificial intelligence and machine learning has been significant. It has reduced the human workload improved quality of life significantly. This article describes the use of artificial intelligence and machine learning to augment drug discovery and development to make them more efficient and accurate. In this study, a systematic evaluation of studies was carried out; these were selected based on prior knowledge of the authors and a keyword search in publicly available databases which were filtered based on related context, abstract, methodology, and full text. This body of work supported the roles of machine learning and artificial intelligence in facilitating drug development and discovery processes, making them more cost-effective or altogether eliminating the need for clinical trials, owing to the ability to conduct simulations using these technologies. They also enabled researchers to study different molecules more extensively, without any trials. The results of this paper demonstrate the prevalent application of machine learning and artificial intelligence methods in drug discovery, and indicate a promising future for these technologies; these results should enable researchers, students, and pharmaceutical industry to dive deeper into machine learning and artificial intelligence in a drug discovery and development context.

International audience; Situated visualization is an emerging concept within visualization, in which data is visualized in situ, where it is relevant to people. The concept has gained interest from multiple research communities, including visualization, human-computer interaction (HCI) and augmented reality. This has led to a range of explorations and applications of the concept, however, this early work has focused on the operational aspect of situatedness leading to inconsistent adoption of the concept and terminology. First, we contribute a literature survey in which we analyze 44 papers that explicitly use the term "situated visualization" to provide an overview of the research area, how it defines situated visualization, common application areas and technology used, as well as type of data and type of visualizations. Our survey shows that research on situated visualization has focused on technology-centric approaches that foreground a spatial understanding of situatedness. Secondly, we contribute five perspectives on situatedness (space, time, place, activity, and community) that together expand on the prevalent notion of situatedness in the corpus. We draw from six case studies and prior theoretical developments in HCI. Each perspective develops a generative way of looking at and working with situatedness in design and research. We outline future directions, including considering technology, material and aesthetics, leveraging the perspectives for design, and methods for stronger engagement with target audiences. We conclude with opportunities to consolidate situated visualization research.

Objective: To explore publicly available information about the self-removal of long-acting reversible contraception (LARC) on a popular video-sharing website. Study Design: We conducted a comprehensive keyword search of YouTube videos related to self-removal of long-acting reversible contraception (LARC)—namely intrauterine devices (IUDs) and implants. We analyzed video content to explore demographic characteristics, method and duration of LARC use, and motivations and experiences of self-removal. Results: Our keyword search identified 58 videos that met the criteria for inclusion, including 48 videos that featured individuals who removed an IUD and 10 who removed an implant. Collectively, videos had over 4 million views. We identified most video creators as white (53.4%), 31% as Black, and 14.3% as Latinx. Reasons for LARC discontinuation included negative side effects, fear of potential side effects, and desire for pregnancy. Users were motivated to remove their own device by both preferences and barriers to formal care. Fifty-six individuals (96.6%) successfully removed their device, and most described their experience in positive terms related to the ease of removal. Conclusion: This study builds upon prior research by describing publicly available information about LARC self-removal. The over-representation of Black women in our sample may reflect a higher prevalence of LARC self-removal among this population. Positive experiences of self-removal and high levels of viewer engagement with online videos suggest a greater need for provider counseling on LARC removal at the time of insertion. Implications: Prior to LARC insertion, patients should be made aware of any financial requirements for discontinuation. Provider counseling for self-removal at the time of insertion will likely minimize health risks and affirm patient reproductive autonomy.

With the outbreak of e-mail message leakage events, such as the Hillary Clinton's Email Controversy, privacy and security of sensitive e-mail information have become users' primary concern. Encrypted email seems to be a viable solution for providing security, but it will greatly limit their operations. Public encryption with keyword search (PEKS) scheme is a popular technology to incorporate security protection and favorable operability functions together, which can play an important role in searching over encrypted email in a cloud server. In this paper, we propose a practical PEKS scheme named as public-key multi-keyword searchable encryption with hidden structures (PMSEHS). It could enable e-mail receivers to do the multi-keyword and boolean search in the large encrypted email database as fast as possible, without revealing more information to the cloud server. We also give comparative experiments, which demonstrate that our scheme has a higher efficiency in multi-keyword search for encrypted emails.

Dynamic Searchable Symmetric Encryption (DSSE) has gained increasing popularity as it enables users to perform both file updates and ciphertext retrieval over encrypted data . However, existing DSSE schemes still lead to privacy leakage ( e.g., forward and backward privacy) in the dynamic setting. Some forward and backward secure DSSE schemes have been proposed, but still cannot support the keyword shielding flexibly. To solve this challenging issue, we propose a Forward and Backward Authorized Keyword Search (FB-AKS) scheme with recoverable keyword shielding by using trapdoor permutations and puncturable encryption in this paper. Compared with existing forward and backward private schemes, FB-AKS achieves keyword authorization flexibly ( e.g., keyword shielding, keyword un-shielding). The formal security analysis proves that FB-AKS achieves forward and backward security. And extensive experiments demonstrate that FB-AKS has less computation and storage overheads .

With the rapid growth and adoption of cloud computing, more sensitive information is centralized onto the cloud every day. For protecting this sensitive information, it must be encrypted before being outsourced. Current search schemes allow the user to query encrypted data using keywords, but these schemes do not guarantee the privacy of queries (i.e., when the user hits query more than once with the same keywords, the server can capture information about the data). This paper focuses on the secure storage and retrieval of ciphered data with preserving query privacy. The proposed scheme deploys the sparse vector space model to represent each query, which focuses on reducing the storage and representation overheads. And the proposed scheme adds a random number to each query vector. Hence, the cloud server cannot distinguish between queries with the same keywords, which ensures the privacy of the query. Experimental results show that the proposed scheme outperforms other relevant state-of-the-art schemes.

BACKGROUND Biliary cystadenomas are very rare benign tumors which can transform into cystadenocarcinomas. The largest case series reported on 221 cases over 30 years from 10 HPB centers, i.e., about 7 cases per center per decade. The recommended treatment is liver resection. Enucleation of biliary cystadenomas has been done rarely. The purpose of the study was to determine the outcome of enucleation of these cysts, particularly the mortality rate and the recurrence rate. METHODS A keyword search was done using OVID followed by a search of the bibliography of papers describing the enucleation of biliary cystadenomas. Of 45 articles obtained, 25 were retained. The main reasons for exclusion were non-English language and review articles. RESULTS One hundred three patients in the 25 studies were treated with enucleation. Thirteen studies described prior treatments that had failed with resulting recurrence requiring re-treatment. The main indication for enucleation was large central cysts for which liver resection would be high risk. There were no postoperative deaths in patients treated by enucleation. Thirteen studies provided long-term follow-up in 40 patients, a substantial number given the rarity of the tumor. There were no recurrences or transformations to malignancy. CONCLUSIONS Enucleation seems to represent a reasonable treatment technique for BCA, especially when a large cystic lesion is located centrally and/or would require a large liver resection with significant loss of parenchyma.

In cloud computing, enabling search directly over encrypted data is an important technique to effectively utilize encrypted data. Most of the existing techniques are focusing on fuzzy keyword search as it helps achieve more robust search performance by tolerating misspelling or typos of data users. Existing works always build index without classifying keywords in advance. They suffer from efficiency issue. Furthermore, Euclidean distance or Hamming distance is often chosen to evaluate strings’ similarity, ignoring prefixes matching and the influence of strings’ length on the accuracy. We propose an efficient fuzzy keyword search scheme with lower computation cost and higher accuracy to address the aforementioned problems. We employ the sub-dictionaries technique and the Bed-tree structure to build an index with three layers for achieving better search efficiency. With this index structure, the server could locate the keyword and could narrow the search scope quickly. The Jaro-Winkler distance is introduced to qualify the strings’ similarity by considering the prefixes matching and string length. The secure privacy mechanism is incorporated into the design of our work. Security analysis and performance evaluation demonstrate our scheme is more efficient compared to the existing one while guaranteeing security.

To maintain the anonymity of users, cloud storage owners often outsource encrypted documents. As a consequence, it is important to establish efficient and precise cypher text search techniques. One issue would be that the connection between documents is typically obscured during the encryption process, resulting in a significant deterioration of search accuracy efficiency. Additionally, the volume of data stored in data centers has exploded. This will make it significantly more difficult to create cipher text search schemes capable of providing efficient and reliable online information retrieval on large quantities of encrypted data. The paper proposes a hierarchical clustering approach in order to accommodate additional search semantics and to satisfy the demand for fast cipher text search in a big data environment. The proposed hierarchical approach clusters documents according to their minimum importance levels and then sub-clusters them until the maximum cluster size is reached. This approach can achieve linear computational complexity throughout the search process, spite of the fact that its size of the record set grows exponentially. The minimum hash sub-tree structure is used in this paper to check the validity of search results. The results demonstrate that as the number of documents in the dataset increases, the proposed method's search time increases linearly, while the conventional method's search time increases exponentially. Additionally, the suggested method outperforms the standard method in terms of rank privacy and document relevance.

In this paper we present a survey on keyword based searching algorithms. Various searching techniques are used for retrieving the encrypted data from cloud servers. This survey work involves a comparative study of these keyword based searching algorithms. It concludes that till now multi-keyword ranked search MRSE scheme is the best methodology for searching the encrypted data.

Cloud based services provide scalable storage capacities and enormous computing capability to enterprises and individuals to support big data operations in different sectors like banking, scientific research and health care. Therefore many data owners are interested to outsource their data to cloud storage servers due to their huge advantage in data processing. However, as the banking and health records usually contain sensitive data, there are privacy concerns if the data gets leaked to un-trusted third parties in cloud storage. To protect data from leakage, the widely used technique is to encrypt the data before uploading into cloud storage servers. The traditional methods implemented by many authors consumes more time to outsource the data and searching for a document is also time consuming. Sometimes there may be chances of data leakage due to insufficient security. To resolve these issues, in the current VP Search(VPS) scheme is implemented, which provides features like verifiability of search results and privacy preservation. With its features the current system consumes more time for file uploading and index generation, which slows down the searching process. In the existing VPS scheme time minimization to efficiently search for a particular document is a challenging task on the cloud. To resolve all the above drawbacks, we have designed an index generation scheme using a tree structure along with a search algorithm using Greedy Depth-first technique, that reduces the time for uploading files and file searching time. The newly implemented scheme minimizes the time required to form the index tree file for set of files in the document which are to be uploaded and helps in storing the files in a index tree format. These techniques result in reducing the document upload time and speeding up the process of accessing data efficiently using multi-keyword search with top-‘K’ value.

Catechol-O-methyl transferase (COMT) enzyme catalyzes the metabolism of dopamine and other catechols in the brain. Several articles investigated catechol-O-methyltransferase (COMT) Val158Met polymorphism as risk factor for alcohol dependence (AD) but the results were inconclusive. The aim of present meta-analysis was to evaluate the association of Val158Met (COMT) polymorphism with AD. Authors performed keyword search of the four electronic databases- Pubmed, Google Scholar, Springer Link and Science Direct databases up to December 31,2019 . Total eighteen studies that investigated the association of Val158Met polymorphism with AD were retrieved. The pooled results from the meta-analysis (2,278 AD cases and 3717 healthy controls) did not show association with AD using all five genetic models (allele contrast model: OR = 1.02, 95% CI= 0.90-1.14, p= 0.03; homozygote model: OR = 1.06, 95% CI= 0.81-1.38, p= 0.69; dominant model: OR = 0.99, 95% CI= 0.85-1.14, p= 0.87; co-dominant model: OR = 0.97, 95% CI= 0.86-1.11, p= 0.71; recessive model: OR = 1.05;95% CI= 0.85-1.29, p=0.61). Results of subgroup analysis showed that Val158Met is not risk for AD in Asian and Caucasian population. In conclusion, COMT Val158Met is not a risk factor for alcohol dependence.

Searchable symmetric encryption (SSE) enables a client to store a database on an untrusted server while supporting keyword search in a secure manner. Despite the rapidly increasing interest in SSE technology, experiments indicate that the performance of the known schemes scales badly to large databases. Somewhat surprisingly, this is not due to their usage of cryptographic tools, but rather due to their poor locality (where locality is defined as the number of non-contiguous memory locations the server accesses with each query). The only known schemes that do not suffer from poor locality suffer either from an impractical space overhead or from an impractical read efficiency (where read efficiency is defined as the ratio between the number of bits the server reads with each query and the actual size of the answer). We construct the first SSE schemes that simultaneously enjoy optimal locality, optimal space overhead, and nearly-optimal read efficiency. Specifically, for a database of size N, under the modest assumption that no keyword appears in more than N1 − 1/loglogN documents, we construct a scheme with read efficiency O(loglogN). This essentially matches the lower bound of Cash and Tessaro (EUROCRYPT ’14) showing that any SSE scheme must be sub-optimal in either its locality, its space overhead, or its read efficiency. In addition, even without making any assumptions on the structure of the database, we construct a scheme with read efficiency O(logN). Our schemes are obtained via a two-dimensional generalization of the classic balanced allocations (“balls and bins”) problem that we put forward. We construct nearly-optimal two-dimensional balanced allocation schemes, and then combine their algorithmic structure with subtle cryptographic techniques.

Safe nursing staffing and patient safety are closely related. A systematic review of the literature was carried out, comparing the number of falls in elderly inpatients in medical-surgical wards with these staffing levels. A review of scientific articles, selected through a keyword search of several electronic databases, showed a direct, although not significant, association between improved nurse staffing and a decrease in the number of falls in elderly inpatients.

It is suspected that diet influences the risk of developing breast cancer. Several β-carotenoids have been inversely associated with breast cancer risk, but association by type of tumor and participant characteristics remain nuclear. The objective of this review of epidemiological studies is to investigate the relationship between β-carotenoids and breast cancer. This review covers the 2014-2020 period and was carried out using the PubMed and EMBASE databases. Only epidemiological studies carried out on β-carotenoids and breast cancer were included. The initial keyword search yielded 1559 results and finally a total of 28 studies were included. The quality of the articles and the risk of bias for each included article were assessed. The selected articles were subsequently classified according to their quality. The evidence from the included studies confirms that there is an association between β-carotenoids and breast cancer risk; the dietary intake of β-carotenoids may be beneficial in reducing the risk of developing breast cancer.

According to several theories, the oro-facial sphere would be interconnected with the rest of the body justifying the requests for care to improve a body zone at a distance. The aim of this literature review was to look for potential distant links of dysmorphoses of the three dimensions of space according to the etiopathogenic theories and the data of science. We carried out a keyword search leading to 58 references. In the transverse dimension, the transverse maxillary hypoplasia and dissymmetry of the molar class of the transverse dimension would not induce a change in the distribution of the weight of the body on a stabilometric platform. In the vertical dimension, hyperdivergent patients have a decreased bite force, cephalic extension with respect to the spine, an extension of the base of the skull, and decreased cervical lordosis. In the anteroposterior dimension, skeletal classes II would be associated with increased cervical lordosis and posterior cephalic extension according to the « true vertical » (inversely for classes III). The prevalence of dental classes II would be increased in scoliosis subjects. Studies with a low level of evidence (grade III, IV or even V) should be interpreted with caution because the simultaneous presence of concomitant anomalies does not allow us to conclude that there is a cause-and-effect relationship.

This initial retrospective study presents information on bacterial and fungal causes of abortion in domestic ruminants in South Africa over 10 years (2006-2016). A complete set of data was collected at the Faculty of Veterinary Science through a keyword search of pathology and bacteriology laboratory registers. Additional electronic data were received from an external laboratory. A total of 288 cases were recorded from six provinces. Overall diagnostic rate was 35.1%. In 14.6% of cases, histological evidence of an infectious process was found, but no aetiological agent was detected. Several cases did not include aetiological diagnoses because applicable diagnostic techniques were not available or not applied when necessary. Increased submission of placenta, as well as additional conventional and molecular diagnostic methods, can contribute to an improved diagnostic rate. In addition, the study highlights the superior significance of Brucella abortus as a major bovine pathogen in South Africa.

Fine-grained searching is an important feature in multi-user cloud environment and a combination of attribute-based encryption (ABE) and searchable encryption (SE) is used to facilitate it. This combination provides a powerful tool where multiple data owners can share their data with multiple data users in an independent and differential manner. In this article, the authors have used key-policy design framework of attribute-based encryption to construct the multi-keyword search scheme where access rights assigned to a data user are associated with his/her secret key. This leads to a situation where a data user can abuse his secret key to distribute it illegally to the unauthorized users to perform search over the shared data which is not intended for him/her. Therefore, to track such kind of key abusers the authors have embedded an extra functionality of tracing the traitors. For this purpose, each user is assigned a unique identity in the form of binary string where each bit represents an attribute related to his identity. In addition to the normal attributes, the access structure of a user also possesses identity-related attributes which are hidden from the user along with some normal attributes. Hence, the proposed scheme supports partial anonymity. Further, in the event of user revocation the proposed scheme efficiently handles the system update process by delegating the computationally intensive tasks to the cloud server. Finally, the proposed scheme is proved secure under Decisional Bilinear Diffie-Hellman (DBDH) assumption and decision linear assumption in the selective security model.

International audience; For better data availability and accessibility while ensuring data secrecy, end-users often tend to outsource their data to the cloud servers in an encrypted form. However, this brings a major challenge to perform the search for some keywords over encrypted content without disclosing any information to unintended entities. This paper proposes a novel expressive authorized keyword search scheme relying on the concept of ciphertext-policy attribute-based encryption. The originality of the proposed scheme is multifold. First, it supports the generic and convenient multi-owner and multi-user scenario, where the encrypted data are outsourced by several data owners and searchable by multiple users. Second, the formal security analysis proves that the proposed scheme is semantically secure against chosen keyword and outsider's keyword guessing attacks. Third, an interactive protocol is introduced which avoids the need of any secure channels between users and service provider. Fourth, due to the concept of bilinear-map accumulator, the system can efficiently revoke users and/or their attributes, and authenticate them prior to launching any expensive search operations. Fifth, conjunctive keyword search is provided thus enabling to search for multiple keywords simultaneously, with minimal cost. Sixth, the performance analysis shows that the proposed scheme outperforms closely-related works.

Scholarly content has become more difficult to find as information retrieval has devolved from bespoke systems that exploit disciplinary ontologies to keyword search on generic search engines. In parallel, more scholarly content is available through open access mechanisms. These trends have failed to converge in ways that would facilitate text data mining, both for information retrieval and as a research method for the quantitative social sciences. Scholarly content has become open to read without becoming open to mine, due both to constraints by publishers and to lack of attention in scholarly communication. The quantity of available text has grown faster than has the quality. Academic dossier systems are among the means to acquire more quality data for mining. Universities, publishers, and private enterprise may be able to mine these data for strategic purposes, however. On the positive front, changes in copyright may allow more data mining. Privacy, intellectual freedom, and access to knowledge are at stake. The next frontier of activism in open access scholarship is control over content for mining as a means to democratize knowledge.

In the era of cloud computing, public key encryption with keyword search (PEKS) is an extremely useful cryptographic tool for searching on encryption data, whose strongest security notion is indistinguishability encryption against chosen ciphertext attack (ind-cca). Adballa et al. presented a transformation from identity based encryption (IBE) to PEKS in the Theory of Cryptography Conference 2010. This paper proposes a new framework of ind-cca secure PEKS in the standard model. Our main technical tool is a newly introduced notion of smooth projective hash function with key mapping, in which the hash key hk is mapped into another mapping projection key mhp besides the classical projection key hp. Finally, we provide an instantiation of our framework based on symmetric eXternal Diffie–Hellman assumption.

Blockchain-based distributed storage enables users to share data without the help of a centralized service provider. Decentralization eliminates traditional data loss brought by compromising the provider, but incurs the possible privacy leakage in a way that the supplier directly links the retrieved data to its ciphertext. Oblivious keyword search (OKS) has been regarded as a solution to this issue. OKS allows a user to retrieve the data associated with a chosen keyword in an oblivious way. That is, the chosen keyword and the corresponding ciphertext are unknown to the data supplier. But if the retrieval privilege is with an authorized keyword set, OKS is unavailable due to one-keyword restriction and public key encryption with keyword search (PEKS) might lead to high bandwidth consumption. In this paper, we introduce Searchain, a blockchain-based keyword search system. It enables oblivious search over an authorized keyword set in the decentralized storage. Searchain is built on top of a novel primitive called oblivious keyword search with authorization (OKSA), which provides the guarantee of keyword authorization besides oblivious search. We instantiate a provably secure OKSA scheme, featured with one-round interaction and constant size communication cost in the transfer phase. We apply OKSA and ordered multisignatures (OMS) to present a Searchain protocol, which achieves oblivious peerto-peer retrieval with order-preserving transaction. The analysis and evaluation show that Searchain maintains reasonable cost without loss of retrieval privacy, and hence guarantees its practicality.

Introduction Over the past 20 years, evidence has emerged indicating oral isotretinoin could be considered a potential treatment for photoaged skin. In this review, we provide a succinct overview of the available evidence and provide commentary on the current and future directions for utilizing oral isotretinoin as a potential treatment for photoaging. Methods We prepared a review protocol and searched the PubMed and Cochrane databases for relevant literature published between January 1982 and April 2020. Using a defined keyword search, a total of 23 papers were initially identified by the main author. Two authors independently reviewed each of the 23 articles, and 6 articles were deemed relevant to this study. Results Of the six studies included in this review, three were randomized clinical trials, one was a nonrandomized clinical trial and two were prospective cohort studies. All studies were conducted between 2000 and 2015. Across all 6 studies, 251 patients were recruited, with a mean of 42 patients per study. Four studies were in favor of isotretinoin to improve photoaged skin, 1 study showed no benefit, and 1 study showed no benefit when compared to topical tretinoin treatment. Of the studies available, many were hampered by methodological challenges. Conclusion Oral isotretinoin may be useful for treating photoaging but there is currently insufficient evidence to support its use. In comparison with other established anti-photoaging treatments, it is not clear whether the potential benefits of oral isotretinoin outweigh the potential risks.

Background Semmelweis reflex is a human behavioral tendency to stick to preexisting beliefs and to reject fresh ideas that contradict them (despite adequate evidence). We aim to familiarize the readers with the term that not only has a significant historical background but also grave clinical implications. Methods A keyword search for “Semmelweis reflex,” “Belief perseverance,” “handwashing,” and “Idea rejection” was conducted using PubMed Central, MEDLINE, and Google SCHOLAR. Literature published in paper-based journals and books was also searched. All manuscripts pertaining to these keywords were thoroughly analyzed for this review. Results The first section of our paper briefs the story of Ignaz Semmelweis and brushes on the contributions of other intellectual researchers that were rebuffed initially. The discussion further explains the root cause of this dismissal, an inherent bias against uncertainty that may be at the core of our fear for new ideas. Finally, this review explores the means by which we can prevent ourselves from being a victim of rejection. Conclusions The age-old prejudice that is Semmelweis reflex is explored in this review. With careful and thorough study design, scientific rigor, and critical self-analysis of the manuscript, one can avoid being victimized by this reflex. The dual edged nature of this reflex lays unveiled when its importance is highlighted in the prematurely accepted medical failures. Understanding that any new idea goes through the grill of being critically analyzed and perceived encourages the scientist to hold on to the original thought as it may rather be practice changing.

BACKGROUND: Ventricular assist devices (VADs) have provided a temporising solution to many individuals with refractory heart failure (HF) while awaiting a suitable donor for heart transplantation which remains the gold standard in treatment. Many of the discussions around VADs involve ongoing morbidity; however, one aspect of VADs that is often overlooked is the utility of their log files. We decided to review the literature for mentions of the clinical utility of VAD log files. METHODS: A keyword search was utilised on PUBMED using the terms ‘Ventricular Assist Device’ and ‘Log files’. Perhaps unsurprisingly, this search only yielded 4 results with further articles being discovered through the bibliography of these publications. RESULTS: The 4 identified articles provided basic information on log files, particularly with reference to the HVAD. Logs can be categorised into three types—data (pump parameters), events (changes in parameters) and alarms (abnormal function). Using a combination of these logs, we can readily identify abnormal pump operation such as the development and progression of pump thrombosis, suction events and gastrointestinal bleeding. However, the research potential of log files was not discussed in these publications, particularly as it pertains to areas such as studying speed modulation and pulsatility in VADs. CONCLUSIONS: VADs are an important staple in the treatment of patients with refractory HF. Log files provide a treasure-trove of information and knowledge that can be utilised for clinical benefit. Furthermore, log files provide an excellent tool for conducting research into device functionality. Current literature on the clinical utility of log files is sparse with much untapped potential.

Primary cysts are believed to arise from the splitting of the arachnoid membrane during prenatal development and can be diagnosed in utero. Prenatal diagnosis is uncommon; therefore, the evidence base for counselling expectant mothers is limited. The purpose of this article is to present a case series and review the current literature on prenatally diagnosed arachnoid cysts. A keyword search of hospital electronic records was performed for all patients with a prenatally diagnosed arachnoid cyst at a tertiary neurosurgical centre. Case notes were reviewed for all patients diagnosed between 2005 and 2017. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to structure a systematic review of all English language articles published up to May 2018. A total of eight eligible patients were identified from our own records and 123 from the literature. Sixty-eight per cent of patients had a normal outcome. Sixty-three per cent of patients underwent surgical intervention which was not associated with abnormal outcome. The diagnosis of syndromic/genetic diagnosis (p

Chen et al. indicated the inner keyword guessing attack coming from the low entropy of keywords, which eliminates the semantic security of most keyword search schemes. Then, they accordingly propose the first dual-server PEKS scheme (abbreviated as DS-PEKS) and its related security models to prevent such attacks. In the DS-PEKS architecture, two non-collusive servers must corporate to execute the keyword search procedure. No individual server has the capability of determining the equivalence between keywords alone, and thus the inner keyword guessing attacks can be avoided. In this article, we found that the security models are lack of soundness and strength, so our first result is to define new stronger and sounder security models which implies all security aspects of original models. Secondly, we also propose a generic construction of DS-PEKS schemes based on IND-CCA2 secure PKE schemes. Finally, we analyze the newly proposed DS-PEKS scheme, and proof its security with the stronger models based on the IND-CCA2 security in the standard model.

With the emerging development of cloud computing services, data owners outsource their documents to Cloud Service Providers (CSP) which could lead to threats related to security and privacy. Hence, protecting the privacy of user data and providing queries privacy becomes one of the main concerns of the data owner. One of the solutions for providing privacy and confidentiality of the outsourced data is encrypting it before sending it to the cloud. Although this solution satisfies data confidentiality and prevents the CSP from reading or modifying the data without the data owner's permission, it prevents the data owner to search the outsourced documents directly. Symmetric encryption algorithms e.g. AES have a searching limitation, in which the whole encrypted document needs to be retrieved from the CSP and then decrypt before performing the search procedure. To overcome this limitation, a lot of keyword-based search approaches have been done. These approaches allow users to retrieve just those documents contain special keywords. However, most of these approaches suffer from privacy and security problems and are based on high overhead asymmetric encryption algorithms. This paper proposes a privacy-preserving keyword search scheme for searching over encrypted data. To avoids the high computational cost of asymmetric encryption, the proposed scheme employs symmetric encryption and Bloom filter. Experimental results demonstrate that the proposed searchable encryption algorithm is secure and lightweight, and it has the ability to perform a keyword search over encrypted data without decrypting them.

PurposeOffice workspace is more than a place but one of the essential resources in business organizations. In recent years, research in office workspace management has become an increasingly important scholarly focus. However, there is a dearth of bibliometric studies to date on the subject. This study aims to explore a scientometric analysis of office workspace field.Design/methodology/approachThe title/abstract/keyword search method was used to extract related papers from 1990 to 2018. A total of 1,670 papers published in Scopus were obtained and subjected to scientometric data analysis techniques via CiteSpace software.FindingsThe results revealed the active research institutions and countries, influential authors, important journals, representative references and research hotspots in this field.Practical implicationsWhile this study focused on office workspace management, the findings hold useful implications for the built environment in general and facility management in particular, being a sector that encompasses multiple disciplines involving building, office assets, people, processes and technology, which enable effective functioning of the built facilities.Originality/valueThis is probably the most comprehensive scientometric analysis of the office workspace field ever conducted. This study adds to the so far limited knowledge in the field and provides insights for future research.

Background and objective Accurate identification and categorization of injuries from medical records can be challenging, yet it is important for injury epidemiology and prevention efforts. Coding systems such as the International Classification of Diseases (ICD) have well-known limitations. Utilizing computer-based techniques such as natural language processing (NLP) can help augment the identification and categorization of diseases in electronic health records. We used a Python program to search the text to identify cases of scooter injuries that presented to our emergency department (ED). Materials and methods This retrospective chart review was conducted between March 2017 and June 2019 in a single, urban academic ED with approximately 80,000 annual visits. The physician documentation was stored as combined PDF files by date. A Python program was developed to search the text from 186,987 encounters to find the string “scoot” and to extract the 100 characters before and after the phrase to facilitate a manual review of this subset of charts. Results A total of 890 charts were identified using the Python program, of which 235 (26.4%) were confirmed as e-scooter cases. Patients had an average age of 36 years and 53% were male. In 81.7% of cases, the patients reported a fall from the scooter and only 1.7% reported wearing a helmet during the event. The most commonly injured body areas were the upper extremity (57.9%), head (42.1%), and lower extremity (36.2%). The most frequently consulted specialists were orthopedic and trauma surgeons with 28% of cases requiring a consult. In our population, 9.4% of patients required admission to the hospital. Conclusions The number of results and data returned by the Python program was easy to manage and made it easier to identify charts for abstraction. The charts obtained allowed us to understand the nature and demographics of e-scooter injuries in our ED. E-scooters continue to be a popular mode of transportation, and understanding injury patterns related to them may inform and guide opportunities for policy and prevention.

Objective: To determine the Dentists' practice in compliance with general and guidelines for handling Coronavirus Disease 2019 . Material and Methods: PubMed, Embase, ISI, Scopus, Medicine have been used to search for articles until September 2020. EndNote X9 was used to manage electronic resources as a resource. Joanna Briggs Institute reviewer's manual (JBI) tools was used to assess the quality of studies included in the current systematic and meta-analysis review. The 95% confidence interval (CI) effect size, the random effect model, and the Restricted maximum-likelihood (REML) methods have all been calculated. I 2 values of more than 50% indicated moderate-to-high heterogeneity. Stata/MP v.16 (the fastest version of Stata) statistical software was used to evaluate the Meta-analysis. Results: 39 articles were found in the initial keyword search. The full text of 16 studies was reviewed, and six studies were selected in the end. 72% of participants used a face mask during the dental procedure (72%, 95% CI; 40%-100%). 63% of participants measured fever when patients arrived during the COVID-19 pandemic (63%, 95% CI; 46%-79%). Moreover, 72% of participants used a face mask during the dental procedure (72%, 95% CI; 40%-100%). According to JBI tools, all studies had a moderate risk of bias . Conclusion: The results show that the performance of dental professionals in the conditions of the COVID-19 epidemic is not favorable. Training should be under the standards of treatment guidelines and further measures so that dental professionals can show proper practice by increasing their awareness of this virus and following up on its infection.

Recently, a new generation of P2P systems capable of addressing data integrity and authenticity has emerged for the development of new applications for a "more" decentralized Internet, i.e., Distributed Ledger Technologies (DLT) and Decentralized File Systems (DFS). However, these technologies still have some unanswered issues, mostly related to data lookup and discovery. In this paper, first, we propose a Distributed Hash Table (DHT) system that efficiently manages decentralized keyword-based queries executed on data stored in DFS. Through a hypercube logical layout, queries are efficiently routed among the network, where each node is responsible for a specific keywords set and the related contents. Second, we provide a framework for the governance of the above network, based on a Decentralized Autonomous Organization (DAO) implementation. We show how the use of smart contracts enables organizational decision making and rewards for nodes that have actively contributed to the DHT. Finally, we provide experimental validation of an implementation of our proposal, where the execution of the same protocol for different logical nodes of the hypercube allows us to evaluate the efficiency of communication within the network.

The industrial Internet of Things (IIoT) integrates sensors, instruments, equipment and industrial applications, enabling traditional industries to automate and intelligently process data. To reduce the cost and demand of required service equipment, IIoT relies on cloud computing to further process and store data. Public-key encryption with keyword search (PEKS) plays an important role, due to its search functionality, to ensure the privacy and confidentiality of the outsourced data and the maintenance of flexibility in the use of the data. Recently, Huang and Li proposed the ‘public-key authenticated encryption with keyword search’ (PAEKS) to avoid the insider keyword guessing attacks (IKGAs) in the previous PEKS schemes. However, all current PAEKS schemes are based on the discrete logarithm assumption and are therefore vulnerable to quantum attacks. In this study, we first introduce a generic PAEKS construction, with the assistance of a trusted authority, that enjoys the security against IKGA in the standard model, if all building blocks are secure under standard model. Based on the framework, we further propose a novel instantiation of quantum-resistant PAEKS that is based on NTRU assumption under random oracle. Compared with its state-of-the-art counterparts, the experiment result indicates that our instantiation is more efficient and secure.

With the development of the Mobile Healthcare Monitoring Network (MHMN), patients’ data collected by body sensors not only allows patients to monitor their health or make online pre-diagnosis but also enables clinicians to make proper decisions by utilizing data mining techniques. In MHMN, patients’ personal data are collected by sensors per second and uploaded to the cloud server as multi-dimension vectors, cloud server stores the personal data as well as sends monitoring information to the hospital when the real-time data is abnormal. Hospital users (i.e., doctors, etc.) may query some samples which contain certain textual keywords or digital keywords in certain ranges for disease diagnosis or medical research. For example, a certain hospital user may query all samples with textual keywords ‘cancer; diabetes’ and digital vectors ‘age’ ∈ [30,50], ‘blood sugar’ ∈ [4,8], ‘heart rhythm’ ∈ [70,80]. Besides, the potential value of massive medical data has attracted considerable interests recently, for example, valuable results in diagnosis model can be yield with large-scale aggregation analysis of personal medical data. The cloud server can build a diagnosis model using data mining technology over massive data, so that hospital users or pre-diagnosis users upload medical data (i.e., age, blood pressure, blood sugar, etc.) to the cloud for diagnosis.

Simple Summary The wearable wireless sensor system plays a crucial role in providing behavioral and physiological data for each individual in precision livestock farming. This article reviewed the most types of sensor systems available in the market and summarized detailed information on these systems. Additionally, through meta-analysis, the accuracy of the parameters generated by the sensor system was verified. As a result, it has been shown that there are more than 60 sensor systems of various types have been developed and sold. Most of them generate behavioral and physiological parameters of cattle with excellent performance (e.g., eating time, ruminating time, lying time, standing time, etc.), with the exception of a few parameters (e.g., drinking time and walking time). In this review, it was also investigated that the same parameters predicted by sensor systems of the same brand showed different accuracies, but it was not possible to confirm where this difference originated because the additional experimental conditions presented in the literature were not detailed. Therefore, this review suggested that guidelines for evaluation criteria for research evaluating sensor performance are needed. Abstract The review aimed to collect information about the wearable wireless sensor system (WWSS) for cattle and to conduct a systematic literature review on the accuracy of predicting the physiological parameters of these systems. The WWSS was categorized as an ear tag, halter, neck collar, rumen bolus, leg tag, tail-mounted, and vaginal mounted types. Information was collected from a web-based search on Google, then manually curated. We found about 60 WWSSs available in the market; most sensors included an accelerometer. The literature evaluating the WWSS performance was collected through a keyword search in Scopus. Among the 1875 articles identified, 46 documents that met our criteria were selected for further meta-analysis. Meta-analysis was conducted on the performance values (e.g., correlation, sensitivity, and specificity) for physiological parameters (e.g., feeding, activity, and rumen conditions). The WWSS showed high performance in most parameters, although some parameters (e.g., drinking time) need to be improved, and considerable heterogeneity of performance levels was observed under various conditions (average I2 = 76%). Nevertheless, some of the literature provided insufficient information on evaluation criteria, including experimental conditions and gold standards, to confirm the reliability of the reported performance. Therefore, guidelines for the evaluation criteria for studies evaluating WWSS performance should be drawn up.

We introduce a few-shot transfer learning method for keyword spotting in any language. Leveraging open speech corpora in nine languages, we automate the extraction of a large multilingual keyword bank and use it to train an embedding model. With just five training examples, we fine-tune the embedding model for keyword spotting and achieve an average F1 score of 0.75 on keyword classification for 180 new keywords unseen by the embedding model in these nine languages. This embedding model also generalizes to new languages. We achieve an average F1 score of 0.65 on 5-shot models for 260 keywords sampled across 13 new languages unseen by the embedding model. We investigate streaming accuracy for our 5-shot models in two contexts: keyword spotting and keyword search. Across 440 keywords in 22 languages, we achieve an average streaming keyword spotting accuracy of 87.4% with a false acceptance rate of 4.3%, and observe promising initial results on keyword search.

Despite the increasing attention paid to LEGO® as a learning tool rather than a child’s toy, teaching practices and methodologies for using LEGO® vary according to educational contexts. The purpose of this paper was to investigate the various educational contexts of LEGO® usage in higher education and to identify trends in teaching practices. A systematic literature review was conducted on the use of LEGO® bricks in education and training using an exploratory sampling approach. A total of 298 articles were explored in internationally recognized journal databases using keyword search, and 26 articles were selected for a detailed review. We found a clear distinction in LEGO® usage between learning facilitation and thinking facilitation, as well as between individual application and group application. A simple typology with four quadrants is proposed based on our findings to help novice educators introduce LEGO® into their pedagogical designs.

Background In Roman medicine, face packs, plasters, unguents, and peelings were part of the therapy of dermatological diseases, but also served cosmetic purposes. Ancient medical textbooks inform us about the ingredients for these applications. Beyond medical literature, other genres contain information about dermatological applications. The Roman poet Ovid (43 BC–17 AD) wrote a didactic poem recording five recipes for topical applications for female faces (Medicamina faciei femineae). Researchers debate the relation of Ovid's poem to Roman medicine: Does the poem contain therapeutical or cosmetical information, or is it mere belles lettres? Aims The objective of the paper is to conduct a medico‐historical classification of Ovid's poem by determining whether the ingredients of Ovid's recipes were thought to be effective by the authors of Roman medical textbooks. Methods First, translation and identification of the ingredients were carried out. Second, comparison of the ingredients' functions regarding the therapy of dermatological diseases in two important Roman medical textbooks was realized. For this purpose, several commentaries on the text of Ovid were used and a keyword search in Roman medical textbooks was performed. Results Ovid's five recipes contain 23 ingredients. All ingredients can be found in medical textbooks. We find that 14 of these ingredients serve cosmetic purposes, 17 serve the therapy of dermatological diseases, and 13 serve both. Conclusion Ovid's recipes contain drugs that were considered effective by the authors of Roman medical textbooks. These drugs were recommended both for therapeutic and cosmetic purposes by the same authors. Therefore, Ovid's didactic poem is not mere belles lettres, but contains serious medical and cosmetical information. As far as we know, it is the first Roman text that contains dermatological recipes., publishedVersion

In 2017, the notion of public key authenticated encryption with keyword search (PAEKS) and its security model was defined by Huang and Li. Their main motivation was providing security against inside keyword guessing attacks (KGA). They also proposed a concrete PAEKS scheme secure in their proposed model. In this study, the authors first show that their security model has an important drawback and therefore, cannot handle multi-user settings. As such settings are a necessity in the public-key environment, it is vital to improving the model to capture multiple users. This is what they do in the first part of this study. Then, they consider Huang and Li's PAEKS scheme and prove that it is not secure against inside (and even outside) KGA. Finally, they propose a modified scheme to fix the problem without any additional communication or computation costs. They further prove that the new scheme is secure in the improved model.

Security and privacy are the key issues for the Internet of Things (IoT) systems. Especially, secure search is an important functionality for cooperation among users' devices and non-trusted servers. Public-key encryption with keyword search (PEKS) enables us to search encrypted data and is expected to be used between a cloud server and users' mobile devices or IoT devices. However, those mobile devices might be lost or stolen. For IoT devices, it might be difficult to store keys in a tamper-proof manner due to prohibitive costs. In this paper, we deal with such a key-exposure problem on PEKS and introduce the concept of PEKS with key-updating functionality, which we call key-updatable PEKS (KU-PEKS). Specifically, we propose two models of KU-PEKS: the key-evolution model and the key-insulation model. In the key-evolution model, a pair of public and secret keys can be updated if needed (e.g., the secret key is exposed). In the key-insulation model, the public key remains fixed while the secret key can be updated if needed. The former model makes a construction simple and more efficient than the latter. On the other hand, the latter model is preferable for practical use since a user never updates their public key. We show constructions in each model in a black-box manner. We also give implementation results on Raspberry Pi 3, which can be regarded as a reasonable platform of IoT devices.