cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.j3s9yt
title: Occurrence Download

description: A dataset containing 305188 records in GBIF matching the query:
SELECT PRINTF('%04d-%02d', "year", "month") AS yearMonth,
GBIF_EEARGCode(10000, decimalLatitude, decimalLongitude,
COALESCE(coordinateUncertaintyInMeters, 1000) ) AS eeaCellCode,
speciesKey,
species,
establishmentMeans,
degreeOfEstablishment,
pathway,
COUNT(*) AS occurrences,
COUNT(DISTINCT recordedBy) AS distinctObservers
FROM occurrence
WHERE occurrenceStatus = 'PRESENT'
AND countryCode = 'BE'
AND hasCoordinate = TRUE
AND NOT ARRAY_CONTAINS(issue, 'ZERO_COORDINATE')
AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_OUT_OF_RANGE')
AND NOT ARRAY_CONTAINS(issue, 'COORDINATE_INVALID')
AND NOT ARRAY_CONTAINS(issue, 'COUNTRY_COORDINATE_MISMATCH')
AND "month" IS NOT NULL
AND speciesKey IN (2480242, 9809229, 2495708, 2492526, 2473958, 5231198, 9701857, 2481792, 7634625, 8104397, 2481685, 7745240, 9515886, 9616058, 7788295, 2491534, 2482513, 2490266, 8077224)
GROUP BY yearMonth,
eeaCellCode,
speciesKey,
species,
establishmentMeans,
degreeOfEstablishment,
pathway
ORDER BY yearMonth DESC,
eeaCellCode ASC,
speciesKey ASC

 The dataset's 305188 records were derived from 52 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007767-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.39t3ds
title: Occurrence Download

description: A dataset containing 7039 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Crithmum maritimum L., Lycium intricatum Boiss.)",
 "BasisOfRecord is one of (Specimen, Literature Occurrence, Human Observation, Observation)",
 "Country is Spain",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "CoordinateUncertaintyInMeters is less than 10000",
 {
 "or" : [
 {
 "not" : {
 "EstablishmentMeans" : [
 "is one of (MANAGED, INTRODUCED)"
 ]
 }
 },
 "EstablishmentMeans is null"
 ]
 }
 ]
}

 The dataset includes 7039 records from 32 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007796-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cpsrbd
title: Occurrence Download

description: A dataset containing 304 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Physalaemus signifer (Girard, 1853)"
 ]
}

 The dataset includes 304 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007797-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.27178338
title: Supplementary information for Ultrareliable low-latency slicing in space–air–ground multiaccess edge computing networks for next-generation Internet of Things and mobile applications

description: Article abstractWe study the problem of ultrareliable and low-latency slicing in multiaccess edge computing (MEC) systems for the next-generation Internet of Things (IoT) and mobile applications operating in the space-Air-ground integrated network. The network has a dynamic topology formed by multiple nonstationary nodes with unstable communication links and unreliable processing/transmission resources. Each node can be in one of two hidden states: 1) reliable-in which the node generates no data errors and no losses and 2) unreliable-when the node can generate/propagate random data errors/losses. Solving this problem is difficult, as it represents the nondeterministic polynomial-Time (NP) hard nonconcave nonsmooth stochastic maximization problem which depends on the unknown hidden nodes' states and private information about local, dynamic parameters of each node, which is known only to this node, and not to other nodes. To address these challenges, we develop a new deep learning (DL) model based on the message passing graph neural network (MPNN) to estimate hidden nodes' states. We then propose a novel algorithm based on the online alternating direction method of multipliers (ADMMs)-an extension of the well-known classical 'static' ADMM to dynamic settings, where our slicing problem can be solved distributedly, in real time, without revealing local (private) information of the nodes. We show that our algorithm converges to a global optimum of the slicing problem and has a good consistent performance even in highly dynamic, unreliable scenarios.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DOI: 10.17028/rd.lboro.27178338.v1
title: Supplementary information for Ultrareliable low-latency slicing in space–air–ground multiaccess edge computing networks for next-generation Internet of Things and mobile applications

description: Article abstractWe study the problem of ultrareliable and low-latency slicing in multiaccess edge computing (MEC) systems for the next-generation Internet of Things (IoT) and mobile applications operating in the space-Air-ground integrated network. The network has a dynamic topology formed by multiple nonstationary nodes with unstable communication links and unreliable processing/transmission resources. Each node can be in one of two hidden states: 1) reliable-in which the node generates no data errors and no losses and 2) unreliable-when the node can generate/propagate random data errors/losses. Solving this problem is difficult, as it represents the nondeterministic polynomial-Time (NP) hard nonconcave nonsmooth stochastic maximization problem which depends on the unknown hidden nodes' states and private information about local, dynamic parameters of each node, which is known only to this node, and not to other nodes. To address these challenges, we develop a new deep learning (DL) model based on the message passing graph neural network (MPNN) to estimate hidden nodes' states. We then propose a novel algorithm based on the online alternating direction method of multipliers (ADMMs)-an extension of the well-known classical 'static' ADMM to dynamic settings, where our slicing problem can be solved distributedly, in real time, without revealing local (private) information of the nodes. We show that our algorithm converges to a global optimum of the slicing problem and has a good consistent performance even in highly dynamic, unreliable scenarios.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DOI: 10.15468/dl.3r3u5w
title: Occurrence Download

description: A dataset containing 34757 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Aquila adalberti C.L.Brehm, 1861"
 ]
}

 The dataset includes 34757 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007799-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17028/rd.lboro.27203703
title: Supplementary information for An enhanced block validation framework with efficient consensus for secure consortium blockchains

description: Article abstractConsortium blockchains have attracted considerable interest from academia and industry due to their low-cost installation and maintenance. However, typical consortium blockchains can be easily attacked by colluding block validators because of the limited number of miners in the systems. To address this problem, in this article, we propose a novel block validation framework to enhance blockchain security. In the framework, the block validations are assisted and implemented by various lightweight nodes, e.g., edge devices, in addition to the typical blockchain miners. This improves the blockchain security but can cause an increased block validation delay and, thereby, reduced blockchain throughput. To tackle this challenge, we propose an effective method to select lightweight nodes based on their computing powers to maximize the blockchain throughput, and prove the uniqueness of the optimal nodes selection strategy. Security analysis and simulation results from the deployed consortium blockchain platform show that the proposed framework achieves higher throughput and security than the existing consortium blockchain models.© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DOI: 10.6084/m9.figshare.27129181
title: Production autonomy and sustainability. On the <i>conventionalization</i> of Mediterranean organic livestock

description: <i>Conventionalization</i> of organic farming calls into question its sustainability. No consensus has been reached on the criteria allowing evaluation of this <i>conventionalization</i>. We propose a methodology based on autonomy – a major sustainability attribute from an agroecological perspective. It was applied to Mediterranean beef cattle and pig livestock systems in Spain and led to the differentiation of five models based on their degree of closeness to conventional systems. Semi-intensive white pig systems were the most conventional compared to the extensive <i>dehesa</i> pastureland systems. In most cases, conventionalization derived from the farms’ socioeconomic and institutional context. It is essential to adapt and change public policies in order to improve livestock farm sustainability and to prevent the most vulnerable farmers from disappearing: they are the ones who generate the most valuable ecosystem services. The proposed methodology, based on environmental and socioeconomic indicators, is applicable to assess the conventionalization of other organic systems beyond the Mediterranean.
DOI: 10.6084/m9.figshare.27129181.v1
title: Production autonomy and sustainability. On the <i>conventionalization</i> of Mediterranean organic livestock

description: <i>Conventionalization</i> of organic farming calls into question its sustainability. No consensus has been reached on the criteria allowing evaluation of this <i>conventionalization</i>. We propose a methodology based on autonomy – a major sustainability attribute from an agroecological perspective. It was applied to Mediterranean beef cattle and pig livestock systems in Spain and led to the differentiation of five models based on their degree of closeness to conventional systems. Semi-intensive white pig systems were the most conventional compared to the extensive <i>dehesa</i> pastureland systems. In most cases, conventionalization derived from the farms’ socioeconomic and institutional context. It is essential to adapt and change public policies in order to improve livestock farm sustainability and to prevent the most vulnerable farmers from disappearing: they are the ones who generate the most valuable ecosystem services. The proposed methodology, based on environmental and socioeconomic indicators, is applicable to assess the conventionalization of other organic systems beyond the Mediterranean.
DOI: 10.6084/m9.figshare.26122445
title: <i>Inonotus obliquus</i> aqueous extract inhibits intestinal inflammation and insulin metabolism defects in <i>Drosophila</i>

description: In biomedical research, the fruit fly (<i>Drosophila melanogaster</i>) is among the most effective and flexible model organisms. Through the use of the <i>Drosophila</i> model, molecular mechanisms of human diseases can be investigated and candidate pharmaceuticals can be screened. White rot fungus <i>Inonotus obliquus</i> is a member of the family <i>Hymenochaetaceae</i>. Due to its multifaceted pharmacological effects, this fungus has been the subject of scientific investigation. Nevertheless, the precise mechanisms by which <i>Inonotus obliquus</i> treats diseases remain unclear. In this study, we prepared an aqueous extract derived from <i>Inonotus obliquus</i> and demonstrated that it effectively prevented the negative impacts of inflammatory agents on flies, including overproliferation and overdifferentiation of intestinal progenitor cells and decreased survival rate. Furthermore, elevated reactive oxygen species levels and cell death were alleviated by <i>Inonotus obliquus</i> aqueous extract, suggesting that this extract inhibited intestinal inflammation. Additionally, <i>Inonotus obliquus</i> aqueous extract had an impact on the insulin pathway, as it alleviated growth defects in flies that were fed a high-sugar diet and in <i>chico</i> mutants. In addition, we determined the composition of <i>Inonotus obliquus</i> aqueous extract and conducted a network pharmacology analysis in order to identify prospective key compounds and targets. In brief, <i>Inonotus obliquus</i> aqueous extract exhibited considerable potential as a therapeutic intervention for human diseases. Our research has established a foundational framework that supports the potential clinical implementation of <i>Inonotus obliquus</i>.
DOI: 10.6084/m9.figshare.26122445.v1
title: <i>Inonotus obliquus</i> aqueous extract inhibits intestinal inflammation and insulin metabolism defects in <i>Drosophila</i>

description: In biomedical research, the fruit fly (<i>Drosophila melanogaster</i>) is among the most effective and flexible model organisms. Through the use of the <i>Drosophila</i> model, molecular mechanisms of human diseases can be investigated and candidate pharmaceuticals can be screened. White rot fungus <i>Inonotus obliquus</i> is a member of the family <i>Hymenochaetaceae</i>. Due to its multifaceted pharmacological effects, this fungus has been the subject of scientific investigation. Nevertheless, the precise mechanisms by which <i>Inonotus obliquus</i> treats diseases remain unclear. In this study, we prepared an aqueous extract derived from <i>Inonotus obliquus</i> and demonstrated that it effectively prevented the negative impacts of inflammatory agents on flies, including overproliferation and overdifferentiation of intestinal progenitor cells and decreased survival rate. Furthermore, elevated reactive oxygen species levels and cell death were alleviated by <i>Inonotus obliquus</i> aqueous extract, suggesting that this extract inhibited intestinal inflammation. Additionally, <i>Inonotus obliquus</i> aqueous extract had an impact on the insulin pathway, as it alleviated growth defects in flies that were fed a high-sugar diet and in <i>chico</i> mutants. In addition, we determined the composition of <i>Inonotus obliquus</i> aqueous extract and conducted a network pharmacology analysis in order to identify prospective key compounds and targets. In brief, <i>Inonotus obliquus</i> aqueous extract exhibited considerable potential as a therapeutic intervention for human diseases. Our research has established a foundational framework that supports the potential clinical implementation of <i>Inonotus obliquus</i>.
DOI: 10.5281/zenodo.13918899
title: КРОТОН АЛДЕГИДНИНГ  (2-БУТЕНАЛ) МИҚДОРИЙ АНАЛИЗИ.
DOI: 10.5281/zenodo.13918900
title: КРОТОН АЛДЕГИДНИНГ  (2-БУТЕНАЛ) МИҚДОРИЙ АНАЛИЗИ.
DOI: 10.15468/dl.e5dnpy
title: Occurrence Download

description: A dataset containing 13390 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Arenicola marina (Linnaeus, 1758)"
 ]
}

 The dataset includes 13390 records from 183 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007800-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.4gfftk
title: Occurrence Download

description: A dataset containing 23 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Physalaemus soaresi Izecksohn, 1965"
 ]
}

 The dataset includes 23 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007801-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.akt4cy
title: Occurrence Download

description: A dataset containing 163 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Physalaemus spiniger (Miranda-Ribeiro, 1926)"
 ]
}

 The dataset includes 163 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0007802-241007104925546/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.17632/8vwxnf7rv7.1
title: Genotypes of Human Papilloma Virus in resistant cutaneous warts and their relation to Candida Antigen therapy

description: The scarcity of information about cutaneous wart-associated Human Papilloma virus (HPV) genotypes together with the unmet need for effective therapeutic options are driving a lot of recent research. Intralesional treatment of warts using Candida antigen is an immunotherapeutic approach that has been recently receiving increased attention. The aim of this study is to assess the prevalent HPV genotypes in recalcitrant cutaneous warts and correlate their occurrence to response to Candida antigen immunotherapy.
DOI: 10.17632/8vwxnf7rv7.2
title: Genotypes of Human Papilloma Virus in resistant cutaneous warts and their relation to Candida Antigen therapy

description: The scarcity of information about cutaneous wart-associated Human Papilloma virus (HPV) genotypes together with the unmet need for effective therapeutic options are driving a lot of recent research. Intralesional treatment of warts using Candida antigen is an immunotherapeutic approach that has been recently receiving increased attention. The aim of this study is to assess the prevalent HPV genotypes in recalcitrant cutaneous warts and correlate their occurrence to response to Candida antigen immunotherapy.
DOI: 10.17028/rd.lboro.27203700
title: Supplementary information for Optimizing Age of Information and security of the next-generation Internet of Everything systems

description: Article abstractWe analyze the information exchange and interactions among the major components, i.e., people, things, data, and processes, of the Internet of Everything (IoE) system, where raw data generated by people and things must be processed to obtain relevant higher level information that can be utilized by IoE processes for decision making and actions. Accordingly, the value of information obtained in the IoE system depends on the Age of Information (AoI) - time elapsed from the moment when raw data is generated to the moment when the data is processed and delivered to the processes. To reduce the AoI, the system is realized in the multiaccess edge computing network, where data can be processed by the edge devices (EDs) in proximity to people, things, and processes. The system security and resilience are further enhanced through coded distributed computing when each data input of EDs is encoded with a specific encoding function so that the final result of data processing by EDs can be recovered even if some processing outputs of EDs are erroneous or delayed. We then define a stochastic optimization problem where the AoI, security, and resilience are optimized jointly to maximize the expected long-term system payoff - difference between the value of information and data processing costs. Since this problem is hard to solve directly due to hidden information about the correctness of processing outputs returned by EDs, we develop a machine learning (ML) framework to obtain the problem solution.© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DOI: 10.17028/rd.lboro.27203700.v1
title: Supplementary information for Optimizing Age of Information and security of the next-generation Internet of Everything systems

description: Article abstractWe analyze the information exchange and interactions among the major components, i.e., people, things, data, and processes, of the Internet of Everything (IoE) system, where raw data generated by people and things must be processed to obtain relevant higher level information that can be utilized by IoE processes for decision making and actions. Accordingly, the value of information obtained in the IoE system depends on the Age of Information (AoI) - time elapsed from the moment when raw data is generated to the moment when the data is processed and delivered to the processes. To reduce the AoI, the system is realized in the multiaccess edge computing network, where data can be processed by the edge devices (EDs) in proximity to people, things, and processes. The system security and resilience are further enhanced through coded distributed computing when each data input of EDs is encoded with a specific encoding function so that the final result of data processing by EDs can be recovered even if some processing outputs of EDs are erroneous or delayed. We then define a stochastic optimization problem where the AoI, security, and resilience are optimized jointly to maximize the expected long-term system payoff - difference between the value of information and data processing costs. Since this problem is hard to solve directly due to hidden information about the correctness of processing outputs returned by EDs, we develop a machine learning (ML) framework to obtain the problem solution.© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
DOI: 10.17632/cpvdsy7gw9.1
title: Factors Influencing Chinese Users to use Central Bank Digital Currency payment

description: Factors Influencing Chinese Users to use Central Bank Digital Currency payment
DOI: 10.17632/zwsfc2nrg9.1
title: Factors Influencing Chinese Users to use Central Bank Digital Currency payment

description: Factors Influencing Chinese Users to use Central Bank Digital Currency payment