Protein Data Bank Japan (PDBj, https://pdbj.org/) is the Asian hub of three-dimensional macromolecular structure data, and a founding member of the worldwide Protein Data Bank. We have accepted, processed, and distributed experimentally determined biological macromolecular structures for over two decades. Although we collaborate with RCSB PDB and BMRB in the United States, PDBe and EMDB in Europe and recently PDBc in China for our data-in activities, we have developed our own unique services and tools for searching, exploring, visualizing, and analyzing protein structures. We have also developed novel archives for computational data and raw crystal diffraction images. Recently, we introduced the Sequence Navigator Pro service to explore proteins using experimental and computational approaches, which enables experimental structural biologists to increase their insight to help them to design their experimental studies more efficiently. In addition, we also introduced a new UniProt-integrated portal to provide users with a quick overview of their target protein and it shows a recommended structure and integrates data from various internal and external resources. With these new additions, we have enhanced our service portfolio to benefit both experimental as computational structural biologists in their search to interpret protein structures, their dynamics and function.

Protein Data Bank Japan (PDBj) is the Asian hub of three-dimensional macromolecular structure data, and a founding member of the worldwide Protein Data Bank. We have accepted, processed, and distributed experimentally determined biological macromolecular structures for over two decades. Although we collaborate with RCSB PDB and BMRB in the United States, PDBe and EMDB in Europe and recently PDBc in China for our data-in activities, we have developed our own unique services and tools for searching, exploring, visualizing and analyzing protein structures. We have recently introduced a new UniProt-integrated portal to provide users with a quick overview of their target protein and shows a recommended structure with integrated data from various internal and external resources. The portal page helps users identify known genomic variations of their protein of interest and provide insights into how these modifications might impact the structure, stability and dynamics of the protein. Furthermore, the portal page also helps users to select the optimal structure to use for further analysis. We have also introduced another service to explore proteins using experimental and computational approaches, which enables experimental structural biologists to increase their insight to help them to more efficiently design their experimental studies. With these new additions, we have enhanced our service portfolio to benefit both experimental and computational structural biologists in their search to interpret protein structures, their dynamics and function.

Monitoring changes in greenhouse gas (GHG) emission is critical for assessing climate mitigation efforts towards the Paris Agreement goal. A crucial aspect of science-based GHG monitoring is to provide objective information for quality assurance and uncertainty assessment of the reported emissions. Emission estimates from combustion events (gas flaring and biomass burning) are often calculated based on activity data (AD) from satellite observations, such as those detected from the visible infrared imaging radiometer suite (VIIRS) onboard the Suomi-NPP and NOAA-20 satellites. These estimates are often incorporated into carbon models for calculating emissions and removals. Consequently, errors and uncertainties associated with AD propagate into these models and impact emission estimates. Deriving uncertainty of AD is therefore crucial for transparency of emission estimates but remains a challenge due to the lack of evaluation data or alternate estimates. This work proposes a new approach using machine learning (ML) for combustion detection from NASA’s Black Marble product suite and explores the assessment of potential uncertainties through comparison with existing detections. We jointly characterize combustion using thermal and light emission signals, with the latter improving detection of probable weaker combustion with less distinct thermal signatures. Being methodologically independent, the differences in ML-derived estimates with existing approaches can indicate the potential uncertainties in detection. The approach was applied to detect gas flares over the Eagle Ford Shale, Texas. We analyzed the spatio-temporal variations in detections and found that approximately 79.04% and 72.14% of the light emission-based detections are missed by ML-derived detections from VIIRS thermal bands and existing datasets, respectively. This improvement in combustion detection and scope for uncertainty assessment is essential for comprehensive monitoring of resulting emissions and we discuss the steps for extending this globally.

Land use affects the structure and functioning of forest ecosystems, thus affecting greenhouse gas fluxes. Greenhouse gas emissions were assessed in the Wari-Maro Forest Reserve (FCWM) and its periphery between 2005 and 2020. To achieve this, the methodological approach applied is based on the use of activity data (AD) from 2005 and 2020 land use and land cover maps derived from satellite images and emission factors (EF) from forest inventory data conducted in 2005 and 2020. The analysis of the results shows that the peripheral zone has the highest emission factor evaluated at 87.22 t.eq-CO2 /ha/year against 47.37 t.eq-CO2/ha/year recorded in the Forest Reserve. The total CO2 emissions due to deforestation in the Forest Reserve are 5106.78 t.eq-CO2/ha/year against a global emission of 65402.23 t.eq-CO2/ha/year for the periphery. This high emission of the peripheral area is due to the result of the high anthropogenic pressure in this area. Those due to degradation are 2880.53 t.eq-CO2/ha/year in the Forest Reserve against 1049.67 t.eq-CO2/ha/year in the periphery. The amount of CH4 and N2O increases progressively from the Forest Reserve (319.49 t.eq-CO2/ha/year and 26.80 t.eq-CO2/ha/year) to the periphery (2658.08 t.eq-CO2ha/year and 222.99 t.eq-CO2/ha/year) probably due to the extent of agricultural and livestock production activities in this area.

The Lecturer Team of the IAI As'Adiyah Tadris English Study Program provided assistance in studying English utilizing interactive media at the Wajo Regency Orphanage. The goal of this activity is to increase participants' enthusiasm in learning English by making it more appealing to them. It is intended that through utilizing interactive media, participants would be able to increase their ability to accurately use English terminology. Scrabble is the interactive medium utilized to provide this aid. This activity's data gathering comprises the following: (1) performance test questions to determine the number of participants who have mastered the vocabulary; the test is completed separately by each participant and presented at the conclusion of the learning material. (2) field notes, which involve documenting the English learning process and photographing activities both before and during the action. Based on the mentoring activities that have been completed, it can be concluded that the participants' attitudes have shifted from being less active, unenthusiastic, and less involved to being more active, enthusiastic, and willing to collaborate collaboratively during the mentoring activity, resulting in an increase in the participants' English vocabulary mastery skills.

CO2 emissions from fossil fuel combustion (FFCO2) are conventionally estimated from fuel used (as activity data (AD)) and CO2 emissions factor. Recent traffic emission changes under the impact of the COVID-19 pandemic have been estimated using emerging non-fuel consumption data, such as human mobility data that tech companies reported as AD, due to the unavailability of timely fuel statistics. The use of such unconventional activity data (UAD) might allow us to provide emission estimates in near-real time; however, the errors and uncertainties associated with such estimates are expected to be larger than those of common FFCO2 inventory estimates, and thus should be provided along with a thorough evaluation/validation of the methodology and the resulting estimates. Here, we show the impact of COVID-19 on traffic CO2 emissions over the first six months of 2020 in Japan. We calculated CO2 monthly emissions using fuel consumption data and assessed the emission changes relative to 2019. Regardless of Japan’s soft approach to COVID-19, traffic emissions significantly declined by 23.8% during the state of emergency in Japan (April–May). We also compared relative emission changes among different estimates available. Our analysis suggests that UAD-based emission estimates during April and May could be biased by −19.6% to 12.6%. We also used traffic count data for examining the performance of UAD as a proxy for traffic and/or CO2 emissions. We found the assumed proportional relationship between traffic changes and CO2 emissions was not enough for estimating emissions with accuracy, and moreover, the traffic-based approach failed to capture emission seasonality. Our study highlighted the challenges and difficulties in repurposing data, especially ones with limited traceability/reproducibility, for modeling human activities and assessing the impact on the environment, and the importance of a thorough error and uncertainty assessment before using these data in policy applications.

Abstract The process of archiving mails at the Cihambulu Village office the writing is still conventional. thereare some deficiency including the process of writing that is not neat, archiving still using the ledger.Therefore required a program that can solving the problem, so the problems that occur at thisCihambulu Village office can be resolved. The concept of designing this system refers to the activitiesof data processing incoming mail, data processing outgoing mail, disposition making, to themanufacture of incoming mail reports and outgoing mail. some stages in the development or designof this program are software requirements analysis, program design, program code generation,program testing. The making this program using JAVA programming language, MySQL as databaseand windows 7 as operating system. Research methods used in the design of this system is the methodof interviewing, observation, and literature study. While the purpose of designing this system is toproduce a mail archiving program so that it can assist employees in data processing incoming mail,data processing outgoing mail, disposition making, making reports incoming mails and outgoingmail.

For the implementation of the REDD+ mechanism, the UNFCCC, through decision 12/CP17, invites countries to develop certain tools to estimate reference emission levels for forests. With this in mind, reference emission and absorption levels were estimated in five protected areas in Benin. To achieve this, two different datasets were used, namely: in situ data from the field collection campaign carried out in 2018, especially from the national forest inventory of 2007 and land use data from 2000 to 2018. In accordance with the 2006 IPCC Good Practice Guidance on Greenhouse Gas Inventories, the calculation of historical emissions from deforestation and degradation is done by multiplying Activity Data (AD) by Emission Factors (EF). The analysis of the results shows that at the national level, the annual deforestation rate in protected areas is 0.34% (2091 ha/year), compared to 1.09% (3153 ha/year) for the annual degradation rate. Overall, carbon emissions amount to 166.65 Mt.eq-CO2/ha, or 16.67 Mt.eq-CO2/ha/year, compared to baseline removals of about 1.14 Mt.eq-CO2/ha, or 0.11 Mt.eq-CO2/ha/year in the protected areas covered by this research. Annual emissions of 0.67 Mt.eq-CO2/ha/year from methane are also noted, compared to 0.056 Mt.eq-CO2/ha/year from nitrous oxide. Therefore, It is clear that actions to mitigate GHG emissions must be undertaken directly in Benin’s protected areas in order to strengthen forest carbon stocks.

The library is a facility that serves as a support for student and teacher learning activities. The Library's collection is a textbook that is made a reference to the learning process. In managing data and information, the Library of SMP Negeri 28 Tangerang uses conventional way. This makes the librarian difficult to process data and to display effective information. The purpose of this research makes designing a Web-based library information system to help librarians solve problems in school libraries. Observations, interviews and literature studies are methods used to collect data (need analysis). Meanwhile, prototypes were used to build the school library information System. The result of designing the school library information system is tested using black box testing. The results of this system activity's data, designed the school library information System and the results of information system evaluation. Activity Data in the show in system analysis is running. Design builds an information system is displayed with business process, UML diagram and screen view of a web-based information system. The results of the evaluation indicate that the school library information system can perform fast browsing of data and the information shown in the form of reports is accurate.

Abstract. Emission of greenhouse gases (GHGs) and removals from land, including both anthropogenic and natural fluxes, require reliable quantification, including estimates of uncertainties, to support credible mitigation action under the Paris Agreement. This study provides a state-of-the-art scientific overview of bottom-up anthropogenic emissions data from agriculture, forestry and other land use (AFOLU) in the European Union (EU281). The data integrate recent AFOLU emission inventories with ecosystem data and land carbon models and summarize GHG emissions and removals over the period 1990–2016. This compilation of bottom-up estimates of the AFOLU GHG emissions of European national greenhouse gas inventories (NGHGIs), with those of land carbon models and observation-based estimates of large-scale GHG fluxes, aims at improving the overall estimates of the GHG balance in Europe with respect to land GHG emissions and removals. Whenever available, we present uncertainties, its propagation and role in the comparison of different estimates. While NGHGI data for the EU28 provide consistent quantification of uncertainty following the established IPCC Guidelines, uncertainty in the estimates produced with other methods needs to account for both within model uncertainty and the spread from different model results. The largest inconsistencies between EU28 estimates are mainly due to different sources of data related to human activity, referred to here as activity data (AD) and methodologies (tiers) used for calculating emissions and removals from AFOLU sectors. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.3662371 (Petrescu et al., 2020).

PurposeThe purpose of this paper is to propose the basis for the unification of unmanned aerial vehicle (UAV) group control protocols for the fast deployment of communication network on territories unsuitable for stationary nodes placement.Design/methodology/approachThe paper proposes the application of active data (AD) conception in which the data exist in a form of executable code allowing data packets to control its own propagation through network. The implementation is illustrated for some scenarios of UAV data communication network deployment, i.e., transmission of the AD using navigation functions and dynamic reconfiguration of the nodes.FindingsThe conception of AD expands the range of possible UAV group operations due to on-the-fly adaptation abilities to changes in existing or forthcoming group behavior protocols. This allows the real-time change of data transmission formats, frequency ranges, modulation types, radio network topologies which, in turn, provides the ability to dynamically form the special data transmission networks from a general purpose device temporarily reconfiguring them for data transmission task between transmitter and receiver beyond radio visibility range.Practical implicationsThe paper includes use cases for some situation of UAV data communication network deployment.Originality/valueThe paper aims to expand the UAV group control principles by implementing by rapid adaptation to changes in existing or forthcoming group behavior protocols.

Danish emission values, implied emission factors (IEFs) and activity data (AD) for the national greenhouse gas inventory are assessed according to an updated verification procedure. Focus is on 28 Annex II indicators and 25 identified Key Categories, represented by 29 verification categories covering energy, agriculture, industry and waste. The data are based on the national greenhouse gas inventory for the years 1990 (base year), 2000 and 2010, as reported in 2012, and provided by the United Nations Framework Convention on Climate Change and the European Union. Inter-country comparison and time trend consistency check of Annex II indicators, covering energy and industry, is made for EU15 countries, excluding Italy and Luxembourg. Inter-country comparison and time trend consistency check of IEFs is made for EU15 countries, excluding Luxemburg and including Norway and Switzerland and for some verification steps also including Australia, Canada, Japan, Russian Federation, USA and aggregated values for EU15 ...

Review1. OpenStack OverviewOpenStack [] is open source software (OSS) for centrally and efficiently operating and managing physical servers and devices comprising the cloud.It is under collaborative development by more than 60 companies around the world (as of April 26, 202).The latest version (version 6, Folsom) was released in September 202.Moreover, OpenStack is included in Ubuntu 2.04LTS, a Linux distribution.NTT DATA has been participating in the Open-Stack project since 200 as one of the project startup members.It is conducting research and development (R&D), as well as promoting cloud services using OpenStack together with NTT's R&D laboratories.The service model offered by OpenStack is infrastructure as a service (IaaS), which is a cloud service model suggested by the National Institute of Standards and Technology (NIST) of the USA [2].OpenStack provides users with virtual machines that run on a hypervisor such as kernel-based virtual machines (KVMs) and XenServers.Any OpenStack users can access their virtual machines through networks and operate their computing resources (e.g., central processing units (CPUs), memory, hard disk drives, and IP (Internet protocol) addresses) allocated to their virtual machines.The features of OpenStack are as follows: () Multiple tenants