Project News

[PrimeGrid] Another GFN 19 Found!

On 22 June 2024, 23:51:45 UTC, PrimeGrid's Generalized Fermat Prime Search found the Mega Prime: 9332124^524288+1 The prime is 3,654,278 digits long and will enter “The Largest Known Primes Database” ranked 12th for Generalized Fermat primes and 85th overall. The discovery was made by Detlef Lexut ([SG]KidDoesCrunch) of Germany using an NVIDIA GeForce RTX 3090 in an Intel(R) Core(TM) i9-10940X CPU @ 3.30GHz with 64GB RAM, running Microsoft Windows 11 Professional x64 Edition. This computer took about 27 minutes to complete the probable prime (PRP) test using Genefer23. Detlef Lexut is a member of the SETI.Germany team. The PRP was confirmed prime on 23 June 2024 by an AMD Ryzen 9 5950X @ 3.4GHz with 128GB RAM, running Linux Mint 20.3. This computer took about 15 hours, 43 minutes to complete the primality test using LLR. For more details, please see the official announcement.

View article · Mon, 15 Jul 2024 22:36:13 +0000

[PrimeGrid] GFN 19 Found!

On 19 June 2024, 05:29:47 UTC, PrimeGrid's Generalized Fermat Prime Search found the Mega Prime: 10913140^524288+1 The prime is 3,689,913 digits long and will enter “The Largest Known Primes Database” ranked 11th for Generalized Fermat primes and 81st overall. The discovery was made by Heinrich Podsada (PoHeDa) of Germany using an NVIDIA GeForce RTX 3070 in an AMD Ryzen 9 5950X 16-Core Processor @ 3.40GHz with 64GB RAM, running Microsoft Windows 11 Professional x64 Edition. This computer took about 50 minutes to complete the probable prime (PRP) test using Genefer23. Heinrich Podsada is a member of the SETI.Germany team. The PRP was confirmed prime on 20 June 2024 by an AMD Ryzen 9 5950X @ 3.4GHz with 128GB RAM, running Linux Mint 20.3. This computer took about 15 hours, 56 minutes to complete the primality test using LLR. For more details, please see the official announcement.

View article · Mon, 15 Jul 2024 22:27:37 +0000

[SRBase] BOINC Games sprint 07/15/2024 08:00 (UTC) - 07/18/2024 08:00 (UTC)

If you are a new member create an account over the website.

View article · Mon, 15 Jul 2024 11:24:29 +0000

[SRBase] Trial Factoring 75-76bit range started

The next batch of 50k tests is uploading.

The runtime is now ~2h40min on a RX5500 XT and decreasing on higher ranges.

View article · Thu, 11 Jul 2024 10:02:09 +0000

[SIDock@home] Target # 23: Ebola GP1

Dear participants,

as target # 22 is almost finished, we are glad to introduce the next target. Most of you have voted for Ebolavirus glycoprotein (GP) (174 out of 425 votes, wow!)

The Ebola virus is a highly virulent pathogen responsible for causing Ebola hemorrhagic fever, a severe and often fatal disease. A key factor in the virus's ability to infect host cells and cause disease is its surface glycoprotein (GP), making it an attractive target for antiviral drug development. The Ebola GP is a trimeric protein composed of two subunits per monomer: GP1, responsible for receptor binding, and GP2, which mediates fusion between the viral and host cell membranes. Initially synthesized as a precursor protein, the GP is cleaved by host proteases (furin, cathepsin) into its functional subunits, a process essential for its role in mediating viral entry. The GP facilitates the virus's attachment to the host cell surface, followed by conformational changes that enable membrane fusion, allowing the virus to enter the host cell (to the host endosomal Niemann-Pick C1 (NPC1) receptor or via direct membrane binding; Vaknin et al.; ACS Infect. Dis. 2024, 10, 5, 1590–1601).

Targeting the GP for drug development is advantageous due to its essential role in viral infection, its highly conserved structure among different Ebola virus strains, and the availability of specific binding cavities that can accommodate small-molecule inhibitors. Structural studies using techniques such as X-ray crystallography have identified these binding cavities and elucidated the GP's conformation in both its free and inhibited states. These insights enable the design of drugs that can specifically bind to and inhibit the GP by stabilizing it in its pre-fusion conformation or interfering with its cleavage, thereby preventing the necessary conformational changes for membrane fusion. We will employ high-resolution structures to conduct virtual screening experiments coupled to molecular dynamics simulations to ultimately identify potential GP inhibitors/modulators.

Promising compounds identified through these computational methods will hopefully undergo further validation using biochemical assays, pseudovirus entry assays, and structural analyses to confirm their inhibitory activity. Targeting the GP offers specificity, as it minimizes off-target effects on host cells and reduces the likelihood of resistance development. Moreover, due to the conserved nature of the GP, drugs targeting it could be effective against multiple Ebola virus strains and variants.

We hope that our computations will contribute to the fight against Ebola!

View article · Thu, 11 Jul 2024 09:02:55 +0000

[World Community Grid] Research Update from the MCM team (July 2024)

We continue to characterise lung cancer biomarkers identified in the MCM1 project. This update focuses on ASTN2, a protein involved in neuronal migration. It is expressed across several tissue types, and has been implicated in various cancers.

View article · Wed, 10 Jul 2024 21:25:48 +0000

[PrimeGrid] Project finances

Please visit the forums to find an update on the project finances. Any donations for the project are greatly appreciated. Please visit the donations page if you want to support the project financially. Thank you!

View article · Tue, 18 Jun 2024 10:56:33 +0000

[YAFU] Aliquot sequence 2896896 has terminated!!!

Aliquot sequence 2896896 has terminated!!!

View article · Mon, 17 Jun 2024 17:31:55 +0000

[Climateprediction.net] New batch going out to volunteer's machines: STORMS, investigating how low-pressure systems may change in the future

Project: Quantifying controls on the intensity, variability and impacts of extreme European STORMS
by Clément Bouvier and Victoria Sinclair (University of Helsinki)

Throughout the year, low-pressure systems regularly move across Europe, usually from west to east, bringing cloud, rain and windy weather. Sometimes these weather systems can become very intense, and the winds and rain associated with them can cause damage to buildings and infrastructure, flooding, and can disrupt electricity supply and travel. Although the short-term weather forecasts of these storms are now quite accurate, it still remains uncertain how these storms, and their impacts, are likely to change in the future as our climate changes. Some of this uncertainty is because our understanding of what controls the strength and impacts of these storms is incomplete.

The aim of this project is to understand what controls the strength and structure of these low-pressure systems. We will quantify how the atmospheric state that the low-pressure systems develop in affects the strength and structure of these low-pressure systems. This atmospheric state can be described by various parameters, for example, the mean temperature, moisture content, and upper-level wind speeds (i.e. the strength and width of the jet stream). Since there are lots of different parameters we want to study (not just the ones described above), we want to do lots of experiments in a high controlled manner. Therefore, we will run a large ensemble of simulations of idealised low-pressure systems using the numerical weather prediction model OpenIFS. Although the simulations are idealised, the weather systems that develop look very like real weather systems that we observed in reality. Each ensemble member differs in its initial atmospheric state, and we choose these initial states to cover everything from the current climate to past pre-industrial climates to the most extreme future climate projections. This is exciting because although idealised simulations of low-pressure systems have been performed before, this is the first time that such an extensive exploration of the parameter space will be conducted.

Once we have the results from the large ensemble, we will calculate different measures of the strength of the storms and then use machine learning techniques to see how these relate to the initial states. Our results will hopefully increase in confidence in how these storms and their impacts will change in the future.

Technical information:
Run time: between 8 and 9 hours for 1 workunit (1 core, Xeon Gold 6230)
Number of files: 480 files
Maximum size of individual files: 1.3MB for 2D fields output files, 13.3MB for spectral output files, 7.1MB for 3D fields output files
Total disk load: 2.0GB

View article · Wed, 12 Jun 2024 19:58:43 +0000

[SRBase] The server / project is restarted now

There is a slow progress from rehab but not happy with the results yet. All of the recovering is very slowly with restrictions.

The RAM was tested in the first run and looking ok.

I will test some work too.

I really missed the last pentathlon. Hoping to finish the TF range of GIMPS work too.

View article · Tue, 11 Jun 2024 15:27:16 +0000

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