Following these efforts, the institution informed last November that the number of individuals who have opened digital yuan wallets reached 140 million.Įarlier this week, the digital currency research institute of PBoC released the “e-CNY (Pilot Version)” app – a mobile wallet for the Chinese CBDC – on iOS and Android stores across the country. The People’s Bank of China has been trying to promote its central bank digital currency (CBDC) on numerous occasions throughout the past several months. The authorities have already announced they might allow athletes and foreign visitors to use the financial product during the sports event. The potential expansion of the Chinese CBDC usage comes a few weeks before the start of the Beijing Winter Olympics. “So it makes sense for the central bank to team up with WeChat Pay and Alipay as opposed to doing it on its own,” he concluded. Speaking on the matter, Linghao Bao – Analyst at Consultancy Trivium China – opined that Chinese consumers are so committed to the two companies that they can’t be convinced to switch to a new mobile payment app. Last year, the firm, run by Alibaba affiliate Ant Group, began trials to explore the possible adoption. The company’s move is expected to rapidly increase the number of citizens operating with e-CNY as the firm has nearly 1.2 billion active users.Īlipay – WeChat’s main competitor in China – has also set its focus towards digital yuan settlements. WeChat Adopts Digital Yuan PaymentsĪccording to a recent CNBC report, WeChat Pay – a multi-purpose messaging and mobile payment app – will begin supporting digital yuan settlements. The app has more than one billion users, meaning the initiative could significantly boost the distribution of the digital yuan. China’s leading messaging application – WeChat Pay – will reportedly begin supporting the e-CNY.
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Mac computer with an Intel processor (PPC is supported prior to v9.1.Includes copy prevention and pre-emphasis for each trackĪccording to Apple, one needs to meet the following requirements to install all applications:.Allows for up to 99 tracks and 99 subindexes per track sein, dass Umlaute und Sonderzeichen in den Textbausteinen unvollständig oder verstümmelt dargestellt werden, obwohl die Norm ISO 8859-1 angibt, welche Zeichen mit der Darstellung in derartigen Anzeigen kompatibel sein müssten.Audio CDs created with WaveBurner can be played back on any audio CD player, and can be used as premasters to produce CDs in large numbers for possible distribution. WaveBurner can be used for assembling, mastering, and burning audio CDs. MIDI sequencer and Virtual instrument host Every recording requires a specific single entry in the Studio Recording Database. Learn the essentials of mastering in Studio One with trainer and mastering engineer Joshua Carney Skills: studio one presonus mastering burn audio CD disc ddp 20. This allows users to combine the power of several Macintosh computers to process Logic Pro’s built-in software instruments and plug-ins, and 3rd party processing plug-ins. Waveburner or DSP-Quattro X document(s) (title: ID and description) Waveburner image or DDP image (title: ID and description) After all mixing and mastering is completed and copied to vpaaudio, the copies on local drives should be deleted. PreSonus Studio One 4 is an extremely powerful mastering environment. gigabit Ethernet) this can work in near-real time, depending on buffer settings and CPU loads. Logic will then offload the effects and synth processing to the other machines on the network. One machine runs the Logic Pro app, while the other machines on the network run the Logic node app. The application features distributed processing abilities, which can function across an Ethernet LAN. You can also export DDP files using WaveBurner, while audio CDs created with WaveBurner can be played back on any audio CD player, and can be used as pre-masters for mass production. It features real-time scoring in musical notation, supporting guitar tablature, chord abbreviations and drum notation. Apple has issued a free update for WaveBurner, a Logic Studio application that lets you assemble, master, and burn audio CDs using a SuperDrive or CD burner supported by Mac OS X. Logic Pro can work with MIDI keyboards and control surfaces for input and processing, and for MIDI output. The Space Designer plugin simulates the acoustics of audio played in different environments, such as rooms of varying size, or producing the echoes that might be heard on high mountains. Audio effects include distortions, dynamics processors, equalization filters, and delays. It also supports Apple Loops – royalty-free professionally-recorded instrument loops. Logic Pro provides software instruments, synthesizers, audio effects and recording facilities for music synthesis. Originally created by German software developer Emagic, Logic Pro became an Apple product when Apple bought Emagic in 2002. Logic Pro is a hybrid 32 / 64 bit digital audio workstation and MIDI sequencer software application for the Mac OS X platform. And for that, we need the VLOOKUP function. But, instead of randomly picking a letter, we will look up the letter associated to the customer id. Now that the orders have the id of the customer, we want to know the name of that customer.įor the sake of practice, the names generated will be composed by the word “Company”, followed by a letter/name from the helper data. The customer name will be the first time where we make use of the helper data in the second worksheet. We’ll make them static at the end of the demo. So, write the formula in the first cell of the Customer ID column and then use one of the two methods we’ve seen previously to copy the formula to the remaining 999 cells.Īgain, with each action, you’ll see the numbers being generated again. If you’re using different helper data, then adjust these two limits as needed. In this case I chose to pick a number between 1 and 10 because the helper data contains ten customer names (the data in the second worksheet). As such, our formula is =RANDBETWEEN(1, 10)įriendly tip: if you don’t like using the mouse while writing a formula, press the Tab key to autocomplete the name of functions. The generation of data for this next column is straightforwad, as we are just picking a random customer id by generating a random integer. Whichever one you prefer, please keep in mind these will be the crux of our data generation as they are what allow us to have an arbitrary number of rows of data. Random date generation formula successfully copiedĪnd with these last two sections, we have finished generating the dates for the fake orders and have learned how to copy a formula to multiple cells with two different methods. This is achieved by either pressing Ctrl+D or by selecting the Fill Down option in the menu. Now you have all the cells of the Date column selected, up to the one that already has a date created, and we can fill the empty ones. To select the remaining cells of that column, press the Ctrl+Shift+Up Arrow key combination. This means now you have the last cell of the Date column selected. Move the cursor to the last cell of the Order ID column (Ctrl+Down arrow while having a cell of that column selected) and then press the right arrow. Since we have an adjacent column of the size we want to select, we can do it with simple keyboard shortcuts. Imagine, selecting a thousand rows, by hand. But we are not going to use the mouse for this. ( Copy formula to multiple cells with Fill )įor the first method, using the Fill feature, we need to select all the cells which we want to copy the formula into. The first uses the Fill feature we’ve seen previously, the second is a literal copy and paste after selecting the desired range (by typing the range, not by selecting with the mouse!). What about the remaining 999 orders? Let me show you two ways of achieving this. Okay, all is well, but we have only generated the date for a single order. Don’t worry though, at the end of the demo we’ll make these randomly generated values fixed. Pressing F9 or any interaction with the workbook recalculates the formulas, i.e., generates another random date. However, the cell displays the generated value as a date because we formatted this column in the beginning to be of the date data type. Create a second worksheet by pressing the plus button in the footerīy the way, keep in mind that RANDBETWEEN generates an integer, even if we have given it dates to choose from. By default it has one worksheet, but that first one will be used for our dataset. Open Microsoft Excel and create a new blank workbook. We’ll have that data written in a second worksheet, used exclusively for look up when generating data for our table. Since we’ll need to randomly choose values for our table, such as the quantity purchased, or look up values in a given range, like the price of a product, it would be good to have those values available somewhere to refer to. Now that you’ve been introduced to the demo, let’s talk about the helper data used for look up. Our purpose with this exercise is to become more familiar with manipulating data, both creating new data and making use of already existing data (via look up). A real sales table could never have this structure. However, before going further, please understand the data included in this table is included just for the sake of practicing Excel. For instance, given the customer id, use the name of that customer. The other thing that will be quite important is to have a worksheet from where we can look up values. For the effect, we will mostly make use of random choice of values and number generation. JProfiler has strong support for command line operations. The rich functionality around snapshot comparisons makes it easy to track progress. JProfiler is ideally suited as a QA tool, both during development as well as for dedicated QA teams. With its JEE support, JProfiler bridges the gap between a code profiler and a high-level JEE monitoring tool. For example, in the JEE aggregation level you see the call tree in terms of the JEE components in your application.Īlso, JProfiler adds a semantic layer on top of the low-level profiling data, like JDBC, JMS and JNDI calls that are presented in the CPU profiling views. Thread profiling not only has a separate view section in JProfiler, it is also tightly integrated into the CPU profiling views.Įxcellent support for Java Enterprise Editionĭedicated support for JEE is present in most views in JProfiler. Without a thread profiler, you only have a minimal chance to tackle such issues.Ī whole range of otherwise opaque problems can be solved when using JProfiler, such as increasing liveness in a multi-threaded application that uses too much locking. Problems related to threading are much more frequent than one might assume. Call tree view filters, aggregation levels and thread status selectors are just some examples of JProfiler's versatility in this area. With JProfiler, you have a decisive advantage when trying to find the reason for a problem. However, CPU data can be overwhelming in its level of detail and the way data is collected can make a huge difference in usability. Questions like why objects are not garbage collected are answered with a single click of the mouse.įixing performance bottlenecks is the most frequent use case for a profiler. Each view provides you with essential insights on the selected objects. 5 different views show different aspects of the current set of objects.Įach view allows you to create new object sets based on the displayed data. JProfiler's heap walker offers you an intuitive interface to solve both simple and complex memory problems. In addition, you can save snapshots at any time, interactively as well as programmatically.įinding a memory leak can be impossible without the right tool. CPU, memory and thread profiling views are updated live and can be inspected without the need to wait for the measurement to complete.įor a large number of use-cases, this ability provides you with an extremely fast path to a solution. With JProfiler you can immediately observe profiling data as your application is running. On all levels, JProfiler has been carefully designed to help you get started with solving your problems. JProfiler is just that: simple and powerful at the same time.Ĭonfiguring sessions is straight-forward, third party integrations make getting started a breeze and profiling data is presented in a natural way. At the same time, you do not want to spend time learning how to use the tool. When you profile, you need the most powerful tool you can get. JProfiler's intuitive GUI helps you find performance bottlenecks, pin down memory leaks and resolve threading issues. JProfiler is an award-winning all-in-one Java profiler. An award-winning all-in-one Java profiler A scoping review of currentlyĪvailable m-apps in Nigeria, revealed none which support agroecology. Peer-to-peer knowledge exchange is a key aspect of this approach and mobileĪpplications (m-apps) could be used to facilitate this. Therefore, this studyĮxplored potential options to facilitate a bottom-up approach to agroecological transition. Policy, this is difficult to influence and change in the short-term. As the top-down information AKIS is driven by government Intensive or conventional farming techniques and there was no expertise within the NEARLS personnel revealed that government agricultural policy was based solely on The National Extension and Advisory Liaison Service. Innovation is provided to farmers through the extension services. Currently, information on agricultural techniques and The extension services and a bottom-up, informal system of peer-to-peer knowledgeĮxchange between farmers. Strands, a top-down formal system determined by government policy and facilitated by The examination of theĮxisting agricultural knowledge exchange systems (AKIS) in Nigeria identified two clear To determine if this is replicated in other regions of Nigeria. The farmers interviewed in this study were not familiar with the termĪgroecology although they understood what organic agriculture was and were concernedĪbout the impact of conventional practices on their environment. In total, 70 participants took part in the study, this comprised of 40įarmers, 20 extension personnel and 10 agricultural university lecturers, purposively and The fieldwork research activities took place in Imo and Abia states, in Qualitative methods were successfully utilised for dataĬollection and analysis, these included focus groups, semi-structured interviews and Rationale for the study and justification for the methods chosen as this project intersectsĪt different research fields. Participatory action and design science research. This study adopted an inductive approach which incorporates From theseĪims, five objectives were developed, and these were addressed using a variety of Understood in Nigeria 2) to evaluate the opportunities for wider adoption ofĪgroecological techniques and 3) to understand the challenges to transitioning from theĬurrent conventional farming system to a more agroecological approach. Study had three broad aims: 1) to understand how agroecology is practised and Increasing global food and environmental crises, particularly inĪfrica, have created renewed interest in the viability of alternative approaches toĪgriculture and food systems such as agroecology for ameliorating these issues. Despite all these efforts, Nigeria remains a food deficit nation and a net importer Little to support smallholder farmers and have resulted in negative environmental Based on conventional agricultural techniques these policies have done Production, various agricultural policies and programmes have been introduced by the Over the last four decades in a bid to enhance agricultural Nigeria is still predominantly an agrarian society the agricultural sector employs aroundĤ0% of the entire labour force. Implications for practice, policy, and research are discussed. The results suggest that increasing mobile phone services in rural Nigeria enhances farmers' knowledge, information, and adoption of improved farm inputs and by extension, spurs rural informal sector economic activities in sub‐Saharan Africa. However, results also show that the impact of mobile phones (as a channel to accessing and using modern agricultural inputs) is contingent on how mobile networks are able to link farmers who live in rural areas and work mainly in farming. Results from the use of a bivariate probit model indicate that the mobile phone‐based technology via the e‐wallet program is a critical factor that has enhanced farm entrepreneurship in rural Nigeria. One thousand one hundred and fifty‐two rural farmers were sampled across the six geopolitical zones of Nigeria. The research is motivated by the absence of literature focusing on the problem statement or objective of the study. Informal sector farmers are those that are not legally registered at the national level although could be connected to a registered association. The objective of this investigation is to assess the impact of the Federal Government of Nigeria (FGN) e‐wallet program on informal farm entrepreneurship development in rural Nigeria. Transforming agriculture from a largely subsistence enterprise to a profitable commercial venture is both a prerequisite and a driving force for accelerated development and sustainable growth in sub‐Saharan Africa.
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Index="dc_green_idx" event=A OR event=B OR event=C OR event=D | fields index invite event TimeSubmitted | stats latest(TimeSubmitted) as TimeSubmitted, latest(eval(case(event="A",TimeSubmitted))) as A_TimeSubmitted values(event) as event by invite | where mvcount(event)>3 and isnull(A_TimeSubmitted) | sort - TimeSubmittedĪlthough, really, unless you need the Time_submitted from A for some other reason, you could just go with this: So, this is what it seems like you are trying to do: Given your code, any invite that had any events other than A would get "yes" in BUnsupp. Do we need to use service accounts for Splunk enterprise components like Indexer or local accounts are fine. I am suspecting a problem with local account. I checked nf file and settings are proper. A multivalue field that is null is not a multivalue field. I am observing a strange behaviour on Splunk where our hot db to cold db transfer is not happening properly. |
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