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Presentation slides given during the CMIP Variables drop in sessionheld on 8th June 2023 at 05:30UTC. Slides provide an overview of CMIP7 planning at the time of the event, as well as updates from the Data Request Task Teamand the discussion points raised to get community feedback on.

This study should determine and analyze the impact of degradation, transfer and promotion, both at the same time and partly, the influence on the implementation of the regional secretary employee in Pinrreg Regency, South Sulawesi. The data in this study uses, whose primary data from the Secretariat's Secretariat of the Pinrag district of a secondary data request list and instruments in this study will be measured using a label scale. The method used is the multiple linear regression analysis used to determine, and both analyze at the same time and partly between the independent variables which affects the dependent variable in this case, which influences the dependent variable in this case, is the implementation of regional Secretary Employees in Pinrang Regency, South Sulawesi. The results of this study. With regard to the results of this study, there is no partial impact of degradation about performance, as degradation is rarely treated as a sanction of employees, mutations have a partial significant impact on performance, this is because mutations are usually carried out, While promotions are not used not clearly its effect on performance during promotions this is the result of the bore promotion with a low program is given by the agency, of course, has an impact on the low performance of the employees, while the test results show simultaneously that the three Variables, namely, the variables, mutation and promotion of position, influence the performance of employees at the Pinrreg district counselor office

This file describes the list of output variables to be provided for the Aerosol realm for the RCM simulations of the Med-CORDEX-CMIP6 initiative

The problem in this study is the effect of organizational commitment and the application of good governance principles on service quality. This research is located at the Research and Development Planning Agency of Banjarnegara Regency, this study aims to explain the influence of organizational commitment variables and the application of good governance principles in a passive and simultaneous way on service quality. This research is a quantitative research. The data used in this study is primary data with a questionnaire technique. The population in this study are people who carry out research permits and data request permits in the Research, Development and Planning Program. The sampling technique in this study is to use the slovin calculation and obtained a sample of 100 respondents. Data analysis in this study used multiple linear regression analysis with SPSS 24 software. The results of this study indicate that partially the organizational commitment variable has no effect on service quality and the variable application of the principles of good governance has a positive and significant effect on service quality. Meanwhile, simultaneously organizational commitment and the application of good governance principles affect service quality.

Objective To compare two strategies for requesting additional information for systematic reviews (SR) from study authors. Study design and setting Randomised study within a SR of hospital volume-outcome relationships in total knee arthroplasty. We sent personalized email requests for additional information to study authors as either email text (“Email” group) or attachment with self-developed, personalised data request forms (“Attachment” group). The primary outcome was the response rate, the secondary outcomes were the data completeness rate and the reviewer time invested in author contact. Results Of 57 study authors, 29 were randomised to the Email group and 28 to the Attachment group. The response rate was 93% for Email and 75% for Attachment (odds ratio 4.5, 95% confidence interval [0.9–24.0]). Complete data were provided by 55% (Email) vs. 36% (Attachment) of authors (odds ratio 2.2 [0.8–6.4]). The mean reviewer time was shorter in the Email (mean ± standard deviation of 20.2±14.4 minutes/author) than the Attachment group (31.8±14.4 minutes/author) with a mean difference of 11.6 [4.1–19.1] minutes/author. Conclusion Personalised email requests elicited high response but only moderate data completeness rates regardless of the method (email text or attachment). Email requests as text took less reviewer time than creating attachments.

Encouraging consumers to enter a data disclosure process constitutes a crucial challenge for retailers. This paper suggests that retailers can lever consumers’ willingness to enter disclosure processes through the design of their data requests. Four experimental studies confirm that consumers are more likely to comply with a data request if retailers do not only use textual relevance arguments but also augment them with relevance-illustrating game elements to further underpin the purpose of data disclosure. This favorable effect can be delineated according to dual-processing models of decision-making: Relevance-illustrating game elements amplify the positive effect of textual relevance arguments by helping consumers to a) cognitively appreciate the objective benefits of data disclosure (i.e., meaningful engagement) and b) increase hedonic engagement on the affective processing route. However, arbitrarily chosen game elements which solely aim at entertaining without conveying the purpose of data disclosure, do not yield these positive effects. Finally, the authors show that the proposed approach is especially worthwhile for retailers facing customers with low trust levels, whereas customers with high trust levels are likely to comply with the data request regardless.

Vehicles in urban city are equipped with more and more sensing units, and sensed data are continuously generated in large amount. These sensed data could be filtered and preprocessed before being shared or uploaded to the road side units and the cloud for efficiency. In this paper we propose a filter-based framework called FERA (Filter-based Efficient Request Answering), which combines the concept of fog computing and vehicular sensing, and adopts the pull/push strategies to adaptively and efficiently gather the requested data in vehicular ad hoc networks. Filters are defined based on the ratio of cost between the push and the pull methods to control the passage or blockage of the data readings. Moreover, filter cubes are defined to manage large number of filters, where efficient algorithms are developed to construct, update and store the filter cubes so that the matched data readings are pushed upward and unmatched data readings are blocked effectively. Extended simulated experiments demonstrate the proposed scheme has a much higher success ratio of request answering than existing schemes, e.g. REED (Abadiet al., 2005) and GeoVanet (Delotet al., 2011). Up to 94 percent of the requests could be successfully processed, while at the same time maintaining a relatively low query cost.

Japanese encephalitis (JE) is one of the zoonotic arbovirus diseases through mosquito bitescauses brain inflammation in humans,mental disability,that can ultimately lead to death. Each year there are about 50,000 cases of JE in Asia with 10,000 deaths. The incidence of Japanese encephalitis in humans has never been reported in South Sumatra. Further analysis to see the effect of temperature, air humidity, wind speed, and weather conditions to the density of mosquito confirmed of JE virus in South Sumatera Province. The method used in this advanced analysis is to submit a data request to the data management of the Research and Development Agency through submission of a data set request. Instruments in this further analysis are Form N-01 (Mosquito Ecosystem), Form N-02 (Human Feed), Form N-03 (Animal Feed), Form N-04 (Animal Baited Trap Net) Vectora Special Research 2015. Analysis data is done by using linear regression test. Temperature is an environmental factor that affects the density of JE positive mosquitoes in theLahat and OKI District. Air humidity and wind speed are environmental factors that only affect mosquito density in OKI,weather conditions only affect the density of mosquitoes in Lahat Regency. The greatest correlation factor with the density of mosquitoes is wind speed(r=0,79).

A data request was made from the Health and Social Care Information Centre (HSCIC) regarding patients who had undergone a primary total knee replacement (TKR) at the Norfolk and Norwich Hospital in 2014. In total, 576 patients had received post-operative PROMs questionnaires in 2014. Complete information was available for 195 patients, which forms the basis of this analysis. The patient letters and the pre-operative assessment documentation on our electronic system (Bluespier) were then reviewed. The comorbidities that the clinician felt would apply to that patient were recorded from the list provided in the Oxford Knee Score (OKS) and were then compared with what the patients had recorded. In total, there were 189 additional comorbidities identified from our notes review. Of these, 95 would alter the predicted OKS score in 77 patients. There was a significant change in average predicted OKS score from 33.7 ± 3.9 to 32.3 ± 4.0 (p = 0.02) in the 77 patients who had additional OKS-altering comorbidities. When looking at the case-mix adjustment, the original mean adjustment was -0.83 (± 1.1). After adjusting for clinician-reported comorbidities, there was a significant change in the mean to -1.40 (± 1.4) (p < 0.0001). After the relevant recalculations were carried out, the adjusted average health gain went from 15.254 to 15.907. This is an improvement of 0.653. The small change of ensuring accurate comorbidity recording can have an impact on the adjusted average health gain for a hospital. This is important information: patients report comorbidities differently to clinicians, and often overrate their health. Despite the limitation of this comorbidity data, hospital performance data, which are publically available, are based on this case-mix and comorbidity adjustment. Care clearly needs to be taken in the interpretation of these case mix-adjusted scores. The PROMs (Patient-Reported Outcome Measures) programme, embedded within the NJR, …

The data request of the Coupled Model Intercomparison Project Phase 6 (CMIP6) defines all the quantities from CMIP6 simulations that should be archived. This includes both quantities of general interest needed from most of the CMIP6-endorsed model intercomparison projects (MIPs) and quantities that are more specialized and only of interest to a single endorsed MIP. The complexity of the data request has increased from the early days of model intercomparisons, as has the data volume. In contrast with CMIP5, CMIP6 requires distinct sets of highly tailored variables to be saved from each of the more than 200 experiments. This places new demands on the data request information base and leads to a new requirement for development of software that facilitates automated interrogation of the request and retrieval of its technical specifications. The building blocks and structure of the CMIP6 Data Request (DREQ), which have been constructed to meet these challenges, are described in this paper.

With the wide application of mobile smart devices carried by humans, content dissemination by using Device-to-Device wireless communication technologies in Mobile Opportunistic Networks (MONs) attracts numerous attentions. However, traditional content dissemination approaches have not considered the efficiency of broadcasting interest packets to the providers in MONs with unreliable links. To increase the efficiency of broadcasting interest packets, we propose two data-request-packets broadcasting approaches with the goal of decreasing energy and communication consumption, in which the policy of self-adapting broadcasting time interval is applied. The extensive simulation results show that our proposed approaches greatly prolong the network lifetime, while maintaining higher delivery ratios compared with traditional approach.

The data request of the Coupled Model Intercomparison Project Phase 6 (CMIP6) defines all the quantities from CMIP6 simulations that should be archived. This includes both quantities of general interest needed from most of the CMIP6-endorsed Model Intercomparison Projects (MIPs) and quantities that are more specialised and only of interest to a single endorsed MIP. The complexity of the data request has increased from the early days of model intercomparisons, as has the data volume. In contrast with CMIP5, CMIP6 requires distinct sets of highly tailored variables to be saved from each of the more than 200 experiments. This places new demands on the data request information base and results in a new requirement for development of software that facilitates automated interrogation of the request and retrieval of its technical specifications. The building blocks and structure of the CMIP6 Data Request (DREQ) which has been constructed to meet these challenges is described in this paper.

The increase use of data in the businesses have proved to be profitable but also provides serious threats in form of data leakage, protection and infringement. The company provides sensitive data to the employees but the data is most likely to be leaked. Data protection must be provided to all forms of data. Data protection should be provided in such a way that it strikes balance between data allowance and data rights to the user as well as owner. The level or extent of protection varies with methods used. In this review paper, numerous methods for protecting data from leakage, unauthorized access, unfair use etc. are compared.

The applicant BASF SE submitted a request to the competent national authority in the Netherlands to evaluate the confirmatory data that were identified for bentazone in the framework of the maximum residue level (MRL) review under Article 12 of Regulation (EC) No 396/2005 as not available. To address the data gaps, a new livestock feeding study and storage stability data for bentazone and 6‐hydroxy bentazone in animal matrices were submitted. To address the data gap for potatoes, adjusted less critical good agricultural practices (GAPs) were reported and supporting residue data were provided. The data gap related to analytical methods in fat and herbal infusions were addressed in the framework of the peer review. The data gap for residue trials on leek has not been addressed. Further confirmation from the applicant/Member States are needed for the clarification of the GAP for herbal infusions. Based on the information submitted in support of the confirmatory data request, the existing EU MRLs for bentazone need to be modified for potato and leek, for swine fat and kidney and for bovine, equine, goat and sheep fat, liver and milk. The consumer risk assessment performed in the MRL review was updated, using new toxicological reference values derived by the peer review. No consumer intake concerns were identified.

Data is very important component in the organization and should be managed properly. Information with accurate, precise, and reliable data be beneficial for the organization for decision making. XYZ University realize that the data management is very important process. The needs of data must be supported properly and quickly, so that the required data can be accessed anytime and anywhere. In this study discusses the process of providing data according to user demand. The method in this paper is identification, define the problem, and data collection. XYZ University already has applications to support data requests, but not all data requests can be fulfilled in the system. There is still a process of data requests made through emails. Overall, the application for data requests very helpful for database and system admin staff, so the routine data requests through emails can be reduced. The application has also features for monitoring data requests from units, so the Manager can monitor the process of the data request and find out any unit that doing frequent data requests each month. But, the application also required for tracking data requests, so user can monitor status of data requests, who’s working on, and estimation time for processing data requests. Index Terms - data, data request, database, information system.

The cfdm open-source Python library implements the data model of the CF (Climate and Forecast) metadata conventions and so should be able to represent and manipulate all existing and conceivable CF-compliant datasets.The CF conventions are designed to promote the creation, processing, and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. They cater for data from model simulations as well as from observations, made in situ or by remote sensing platforms, of the planetary surface, ocean, and atmosphere. For a netCDF data variable, they provide a description of the physical meaning of data and of its spatial, temporal, and other dimensional properties. The CF data model is an abstract interpretation of the CF conventions that is independent of the netCDF encoding.The cfdm library has been designed as a stand-alone application, e.g. as deployed in the pre-publication checks for the CMIP6 data request, and also to provide a CF data model implementation to other software libraries, such as cf-python.

The successful development of new technologies for the treatment of rare diseases and the patient access barriers in this field require to revisit the applicability of the traditional health technology assessment approach. The objective of this research was to appraise the evaluation of orphan drugs and to support the improvement of current frameworks, application of additional criteria and the construction of new evaluation schemes. The thesis was based on four independent researches, two systematic literature reviews on disease prevalence and evaluation criteria, and two data analyses, one based on a data request from the public payer in Hungary and one based on orphan drug assessment reports in the United Kingdom.

In this article discussed the application of probabilistic EOQ method using model (q,r) on the control and inventory of anti-pain medication. In this study used data request with the assumption of normal distribution with the aim to determine the reorder point and EOQ to minimize the total cost using the model (q,r) of anti-pain medication Apotek Griya Medika Malang in January to December 2017. After obtaining each the minimum cost of both theoretical and simulated using the original data and the generated data, then the two costs are compared to see which model can obtain the total cost savings by using model (q,r). This method is able to determine the amount of goods to be ordered, the time for effective ordering, and save the total of inventory cost. Keywords: probabilistic EOQ, model (q,r), Apotek Griya Medika Malang, inventory

This paper focus on discussion and design of the LabVIEW-based radiation monitoring system of the Experimental Advanced Superconducting Tokamak (EAST). This monitoring system based on LabVIEW software can get and monitor the environment’s real-time nuclear radiation around EAST. EAST is a fully superconducting Tokamak, it has played an important role of nuclear fusion research and plasma physics experiments. During EAST’s pulse discharge, there will be some radiation produced in the EAST’s hall and environment, so radiation monitoring and control are necessary. Firstly this paper reviews EAST and radiation. Then this paper briefly presents the structure of the monitoring system. Thirdly, the design of the monitoring system based on LabVIEW is presented. The LabVIEW-based radiation monitoring system mainly includes: the definition of serial port, the definition of data request, the definition of data rewrite, the definition of data cutting, the definition of data saving and displaying. This monitoring system can work well.

Background: There is a growing interest in using and analyzing altmetric data for\ud quantifying the impact of research, especially societal impact (Bornmann, 2014, Thelwall\ud et al., 2016, Haunschild and Bornmann, 2017). This study therefore aimed to explore the\ud usefulness of Altmetric.com data as a means of identifying and categorizing the policy\ud impact of research articles from a single center (the University of Sheffield).\ud Method: This study has only included published research articles from authors at the\ud University of Sheffield and indexed in the Altmetric.com database. Altmetric data on\ud policy impact was sourced from Altmetric.com following a data request and included\ud citations up until February 2017. Supplementary Altmetric.com data, including news\ud media, blogs, Mendeley saves, and Wikipedia citations, were also gathered.\ud Results: Altmetric.com data did enable the identification of policy documents that cited\ud relevant articles. In total, 1,463 pieces of published research from authors at the University\ud of Sheffield were found to be cited by between 1 and 13 policy documents. 21 research\ud articles (1%) were listed as being cited in five or more policy documents; 21 (1%) in four\ud policy documents; 50 (3%) in three documents; 186 (13%) in two documents; and 1,185\ud (81%) in one document. Of those 1,463 outputs, 1,449 (99%) were journal articles, 13\ud were books, and 1 was a book chapter (less than 1%). The time lag from the publication\ud of the research to its citation in policy documents ranged from 3 months to 31 years.\ud Analysis of the 92 research articles cited in three or more policy documents indicated\ud that the research topics with the greatest policy impact were medicine, dentistry, and\ud health, followed by social science and pure science. The Altmetric.com data enabled an\ud in-depth assessment of the 21 research articles cited in five or more policy documents.\ud However, errors of attribution and designation were found in the Altmetric.com data.\ud These findings might be generalizable to other institutions similar in organizational structure\ud to The University of Sheffield.\ud Conclusion: Within the limitations of the current text-mining system, Altmetric.com can\ud offer important and highly accessible data on the policy impact of an organization’s\ud published research articles, but caution must be exercised when seeking to use this\ud data, especially in terms of providing evidence of policy impact.

In this paper, we present an efficient data channel assignment (DCA) scheme for a mixed cell (i.e., a 3G cell with embedded WLANs). Our effort is essential to increase the data request (i.e., a call) handling capacity in 3G systems, with a ‘low request dropping probability’. In UMTS-first DCA scheme prefers 3G channel in dual coverage and reduces vertical handoffs from 3G to WLAN. But it deprives some users of high speed service of WLAN even when WLAN facility is available. On the contrary, a WLAN-first DCA scheme overcomes this problem by preferring WLAN system. But the overall call request dropping probability increases with increasing WLAN traffic and at some point, the benefit of WLAN cannot be achieved in a mixed cell. Further, most of the existing models do not consider the reality of non-identical WLAN-hotspots and bidirectional vertical handoffs, restricting the free mobility of the users across 3G and WLAN systems. We propose an improved DCA scheme based on WLAN-first access technique to maximize the usage of WLAN. The proposed model considers the reality of non-identical WLAN-hotspots and allows free mobility between 3G and WLAN. A proposed DCA scheme improves the dropping probability as blocked call request of WLAN are transferred to 3G. Our DCA scheme drops a request only when all the channels of both 3G and WLAN systems are busy. We derive an analytical model for proposed scheme and validate the same with a set of simulation results. We provide an extensive number of numerical results to show that our scheme performs far better than the existing models. The DCA modeling approach can be quite conveniently used for better planning of WLAN hotspots in the mixed cell.

Mobile crowd sensing enables users to collaborate in terms of data collection. In practice, end users collect data through their smart devices and then share it with other users, who find it useful. A data request consists of specific parameters such as location, time or type of data. It is published and users that can fulfill this request send corresponding data, by mainly using their smart-phone as sensing device. While this approach is an interesting alternative when it comes to data collection, it creates a significant privacy concern. In this paper a privacy preserving platform for profitable mobile crowd sensing is presented. Data encryption and bitcoin payments are employed to protect users' privacy. In order to research the users' adoption of such a solution, a survey has been conducted and the results are analyzed.

This operations management case describes a waste-reduction project in a compounding pharmacy in a hospital. Every day, pharmacy technicians prepare a large number of patient-specific medication doses and then deliver these doses to various hospital units. With the rising cost of medications, pharmacy managers become concerned that a significant number of compounded medication doses are not administered to patients and are subsequently wasted. The students are asked to quantitatively evaluate proposed changes to the compounding and delivery process and to estimate savings from process reconfiguration. Two large data sets are provided with the case to facilitate hypothesis generation regarding probable causes of waste and to analyze proposed changes. The analysis will deepen students’ spreadsheet skills as well as mathematical modeling of inventory problems. The case is presented in parts, and it is discussed over one-and-a half class meetings—simulating the steps of a field project: interviewing a client, framing the client’s problem, formulating a data request, and then analyzing the data and delivering a recommendation. This case has been used in a core MBA operations management class; it could also be used in a health-care operations or in a business modeling course. Teaching Note: Interested Instructors please see the Instructor Materials page for access to the restricted materials. To maintain the integrity and usefulness of cases published in ITE, unapproved distribution of the case teaching notes and other restricted materials to any other party is prohibited.

Negligence claims in the UK NHS has increased over the last 30 years. The aim of this present study was determine the number of claims and the cost of litigation in Bariatric Surgery and compare it to similar other specialties. Data was received from NHS Litigation Authority (NHSLA) in response to Freedom of Information data request. There was a total of 7 claims, of which 4 were successful. The total pay out sum was £210,000 in 10 years. This is a very low amount compared to other surgical specialties. This low level of litigation probably indicates that the current bariatric surgical services in the NHS are delivering safe care with good patient satisfaction. This needs to be carefully considered prior to changing the payment tariffs for bariatric surgery.

SummaryIn 2008 it became policy that all those on the care programme approach were assessed for sexual violence/abuse. The implementation of this policy was assessed 8 years on. The findings of a survey and data request to Health and Social Care Information Centre are disappointing. We argue that this important initiative needs to be reinvigorated.

SUMMARY Peer-to-peer (P2P) systems have been developed with the goal of providing support for transparent and efficient sharing of scalable distributed resources wherein size scalability is limited by the costs of all types of transparencies, especially data access transparency, which are due to the need for frequent data exchanges between peers and other related communication overheads. We present a model that formulates the relationship between scalability and data access transparency in P2P distributed systems to figure out how large these systems can be scaled up, given the overheads of establishing data access transparency. To validate our model and show how our model can be deployed in real life, we consider a real P2P distributed system as a case study and evaluate how CPU utilization, bandwidth, and data request frequency parameters of our model relate to the amount of effort required by the system management to establish data access transparency. We then calculate the strength of the coefficient of correlation of scalability and data access transparency in the system. The degree of strength of this coefficient allows the system designer to decide at design time whether to allow the use of the model in the management of system at runtime or not. Copyright © 2012 John Wiley & Sons, Ltd.

Aim The implementation of the new Kidney Allocation Schema (KAS) in Dec. 2014 brought about important changes to deceased donor (DD) kidney allocation. Most notable has been for Highly Sensitized candidates who receive national, regional and local priority based on CPRA. However, the second ranked allocation category, 0-ABDR mismatch (MM), has actually experienced a drop in transplant rates from ∼8.2% pre-KAS to ∼4.7%, 1 yr post-KAS(AJT 16:1834; 2016). As both equity and utility are part of UNOS mission, we sought to assess the racial makeup of 0-ABDR MM recipients and donors. Methods A data request was made via the OPTN web site (optn.transplant.hrsa.gov/data/request-data/) and the returned data-set contained 1,517 0-ABDR mismatched kidney recipients transplanted between 12/04/2014 and 6/30/2017. Demographics collected included: CPRA, Race, Gender and HLA type. Analysis focused on the racial distribution of recipients by the following CPRA groups: 100%, ⩾50 0 Results Among 0-ABDR MM recipients, 47% were females while 60% of the donors were male. The overall racial distribution of DDs for 0-MM recipients was: White: 78.4%, Black: 4.2%, Hispanic: 14.2%, Am Indian-Alaska Native: 0.7%, Hawaiian-Pacific Islander: 0.06% and Multiracial: 0.7% which differs from all DDs. The racial distribution of 0-MM recipients, by CPRA group, is shown in Fig. 1. Conclusions Across all CPRA groups, African Americas (AA) and Asians receive disproportionally fewer 0-ABDR mismatch allografts than Whites or Hispanics when compared to their proportion of the wait list. Among the 100% CPRA group AAs receive more transplants than Hispanics likely due to KAS national allocation policy. However, in all other CPRA groups, Whites and Hispanics receive more allografts than any other group likely due to the racial composition of DDs. Given that the frequency of 0-ABDR MM transplants has dropped significantly since KAS, and the clear racial inequity in allocation, it may be time to reassess the priority/utility of this category. Download : Download high-res image (259KB) Download : Download full-size image