Mutual query data sharing protocol for public key encryption through chosen-ciphertext attack in cloud environment

<p><span>In this paper, we are proposing a mutual query data sharing protocol (MQDS) to overcome the encryption or decryption time limitations of exiting protocols like Boneh, rivest shamir adleman (RSA), Multi-bit transposed ring learning parity with noise (TRLPN), ring learning parity with noise (Ring-LPN) cryptosystem, key-Ordered decisional learning parity with noise (kO-DLPN), and KD_CS protocol’s. Titled scheme is to provide the security for the authenticated user data among the distributed physical users and devices. The proposed data sharing protocol is designed to resist the chosen-ciphertext attack (CCA) under the hardness solution for the query shared-strong diffie-hellman (SDH) problem. The evaluation of proposed work with the existing data sharing protocols in computational and communication overhead through their response time is evaluated.</span></p>

Open Access in Geochemistry from Preprints to Data Sharing: Past, Present, and Future

In this short communication, we discuss the latest advances regarding Open Access in the earth sciences and geochemistry community from preprints to findable, accessible, interoperable, and reusable data following the 14f session held at Goldschmidt conference (4–9 July 2021) dedicated to “Open Access in Earth Sciences”.

Credit and Recognition for Contributions to Data-Sharing Platforms Among Cohort Holders and Platform Developers in Europe: Interview Study

Background The European Commission is funding projects that aim to establish data-sharing platforms. These platforms are envisioned to enhance and facilitate the international sharing of cohort data. Nevertheless, broad data sharing may be restricted by the lack of adequate recognition for those who share data. Objective The aim of this study is to describe in depth the concerns about acquiring credit for data sharing within epidemiological research. Methods A total of 17 participants linked to European Union–funded data-sharing platforms were recruited for a semistructured interview. Transcripts were analyzed using inductive content analysis. Results Interviewees argued that data sharing within international projects could challenge authorship guidelines in multiple ways. Some respondents considered that the acquisition of credit for articles with extensive author lists could be problematic in some instances, such as for junior researchers. In addition, universities may be critical of researchers who share data more often than leading research. Some considered that the evaluation system undervalues data generators and specialists. Respondents generally looked favorably upon alternatives to the current evaluation system to potentially ameliorate these issues. Conclusions The evaluation system might impede data sharing because it mainly focuses on first and last authorship and undervalues the contributor’s work. Further movement of crediting models toward contributorship could potentially address this issue. Appropriate crediting mechanisms that are better aligned with the way science ought to be conducted in the future need to be developed.

Hydroxychloroquine/Chloroquine for the Treatment of Hospitalized Patients with COVID-19: An Individual Participant Data Meta-Analysis

Importance: Results from observational studies and randomized clinical trials (RCTs) have led to the consensus that hydroxychloroquine (HCQ) and chloroquine (CQ) are not effective for COVID-19 prevention or treatment. Pooling individual participant data (IPD), including unanalyzed data from trials terminated early, enables further investigation of the efficacy and safety of HCQ/CQ. Objective: To assess efficacy of HCQ/CQ in patients hospitalized with COVID-19, both overall and in prespecified subgroups. Data Sources: ClinicalTrials.gov was searched multiple times in May-June 2020. Principal investigators of US-based RCTs evaluating HCQ/CQ in hospitalized COVID-19 patients were invited to collaborate in this IPD meta-analysis. Study Selection: RCTs in which: (1) HCQ/CQ was a treatment arm; (2) patient informed consent and/or individual study IRB approval allowed for data sharing; (3) principal investigators/their institutions signed a data use agreement for the present study; and (4) the outcomes defined in this study were recorded or could be extrapolated. Data Extraction and Synthesis: Wherever possible, harmonized de-identified data were collected via a common template spreadsheet sent to each principal investigator, then shared via a secure online data sharing platform to create a pooled data set. When this was not possible, individual study data were harmonized and merged manually. Data were analyzed by fitting a prespecified Bayesian ordinal regression model and standardizing the resulting predictions. Main Outcome(s) and Measure(s): 7-point ordinal scale, measured between day 28 and 35 post-enrollment. Results: Eight of 19 trials met eligibility criteria and agreed to participate. Patient-level data were available from 770 participants (412 HCQ/CQ vs 358 control). Baseline characteristics were similar between groups. We found no evidence of a difference in ordinal scores between days 28 and 35 post-enrollment in the pooled patient population (odds ratio, 0.97; 95% credible interval, 0.76-1.24; higher favors HCQ/CQ), and no convincing evidence of meaningful treatment effect heterogeneity among prespecified subgroups. Adverse event and serious adverse event rates were numerically higher with HCQ/CQ vs control (0.39 vs 0.29 and 0.13 vs 0.09 per patient, respectively). Conclusions and Relevance: The findings of this IPD meta-analysis reinforce those of individual RCTs that HCQ/CQ is not efficacious for treatment of COVID-19 in hospitalized patients.

A Data Sharing and Integration Technology for Heterogeneous Databases

For a long time, there are a large number of heterogeneous databases on the network, and their heterogeneity is manifested in many aspects. With the development of enterprise informatization and e-government, the system database of each department constitutes a real heterogeneous database framework with its independence and autonomy in the network system of many different functional departments. This paper will design information sharing between heterogeneous databases of network database system of many similar functional departments by using XML data model. The solution of data sharing between heterogeneous databases can accelerate the integration of information systems with departments and businesses as the core among enterprises, form a broader and more efficient organic whole, improve the speed of business processing, broaden business coverage, and strengthen cooperation and exchange among enterprises. In addition, heterogeneous database sharing can avoid the waste of data resources caused by the heterogeneity of database, and promote the availability rate of data resources. Due to the advantages of XML data model, the system has good scalability.