The RM85 is the latest in Ebac’s line of rotational molded polyethylene housing dehumidifiers.

España abandona la recesión con vectores de crecimiento creíbles que pueden afianzar la recuperación. Pero el crédito, el consumo y el empleo seguirán estancados.

NetBSD is an open-source, Unix-like operating system known for its portability, lightweight design, and robustness across a wide array of hardware platforms. Initially released in 1993, NetBSD was one of the first open-source operating systems based on the Berkeley Software Distribution (BSD) lineage, alongside FreeBSD and OpenBSD. NetBSD’s development has been led by a collaborative community and is particularly recognized for its “clean” and well-documented codebase, a factor that has made it a popular choice among users interested in systems programming and cross-platform compatibility. ↫ André Machado I’m not really sure what to make of this article, since it mostly reads like an advertisement for NetBSD, but considering NetBSD is one of the lesser-talked about variants of an operating system family that already sadly plays second fiddle to the Linux behemoth, I don’t think giving it some additional attention is really hurting anybody. The article is still gives a solid overview of the history and strengths of NetBSD, which makes it a good introduction. I have personally never tried NetBSD, but it’s on my list of systems to try out on my PA-RISC workstation since from what I’ve heard it’s the only BSD which can possibly load up X11 on the Visualize FX10pro graphics card it has (OpenBSD can only boot to a console on this GPU). While I could probably coax some cobbled-together Linux installation into booting X11 on it, where’s the fun in that? Do any of you lovely readers use NetBSD for anything? FreeBSD and even OpenBSD are quite well represented as general purpose operating systems in the kinds of circles we all frequent, but I rarely hear about people using NetBSD other than explicitly because it supports some outdated, arcane architecture in 2024.

Alianza, Inc.amp;nbsp;today introduced Alianza for Microsoft Teams, a new and powerful solution that gives service providers a robust cloud PBX voice solution for Microsoft Teams.

This paper presents a sequential edge swap (SQES) mechanism to design a robust network for a healthcare system utilising energy and communication range of nodes. Two operations: sequential degree difference operation (SQDDO) and sequential angle sum operation (SQASO) are performed to enhance the robustness of network. With equivalent degrees of nodes from the network's centre to its periphery, these operations build a robust network structure. Disaster attacks that have a substantial impact on the network are carried out using the network information. To identify a link between the malicious and disaster attacks, the Pearson coefficient is employed. SQES creates a robust network structure as a single objective optimisation solution by changing the connections of nodes based on the positive correlation of these attacks. SQES beats the current methods, according to simulation results. When compared to hill-climbing algorithm, simulated annealing, and ROSE, respectively, the robustness of SQES is improved by roughly 26%, 19% and 12%.

File transfer is always handled by a separate service, sometimes it is a third-party service in videoconferencing. When sending files during a video session, file data flow and video stream are independent of each other. Encryption is a mature method to ensure file security. However, it still has the chance to leave footprints on the intermediate forwarding machines. These footprints can indicate that a file once passed through, some protocol-related logs give clues to the hackers' later investigation. This work proposes a file-sending scheme through the video stream using blockchain and steganography. Blockchain is used as a file slicing and linkage mechanism. Steganography is applied to embed file pieces into video frames that are continuously generated during the session. The scheme merges files into the video stream with no file transfer protocol use and no extra bandwidth consumed by the file to provide trackless file transmission during the video communication.

In the present scenario, the security of medical images is an important aspect in the field of image processing. Support vector machines (SVMs) are a supervised machine learning technique used in image classification. The roots of SVM are from statistical learning theory. It has gained excellent significance because of its robust, accurate, and very effective algorithm, even though it was applied to a small set of training samples. SVM can classify data into binary classification or multiple classifications according to the application's needs. Discrete wavelet transform (DWT) and singular value decomposition (SVD) transform techniques are utilised to enhance the image's security. In this paper, the image is first classified using SVM into ROI and RONI, and thereafter, to enhance the images diagnostic capabilities, the DWT-SVD-based hybrid watermarking technique is utilised to embed the watermark in the RONI region. Overall, our work makes a significant contribution to the field of medical image security by presenting a novel and effective solution. The results are evaluated using both perceptual and imperceptibility testing using PSNR and SSIM parameters. Different attacks were introduced to the watermarked image, which shows the efficacy and robustness of the proposed algorithm.

Screen-shooting will lead to information leakage. Anti-screen-shooting watermark, which can track the leaking sources and protect the copyrights of images, plays an important role in image information security. Due to the randomness of shooting distance and angle, more robust watermark algorithms are needed to resist the mixed attack generated by screen-shooting. A robust digital watermarking algorithm that is resistant to screen-shooting is proposed in this paper. We use improved Harris-Laplace algorithm to detect the image feature points and embed the watermark into the feature domain. In this paper, all test images are selected on the dataset USC-SIPI and six related common algorithms are used for performance comparison. The experimental results show that within a certain range of shooting distance and angle, this algorithm presented can not only extract the watermark effectively but also ensure the most basic invisibility of watermark. Therefore, the algorithm has good robustness for anti-screen-shooting.

A new EU BON acknowledging data article provides a virtual species set as a valuable tool in biodiversity monitoring. 

Abstract

Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation. In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a dataset containing more than 700,000 random observations at the extent of Europe. The dataset includes spatial attributes such as: distance to roads, protected areas, country codes, and the habitat suitability of two spatially clustered species (grassland and forest species) and a wide-spread species.

Original Source:

Garzon-Lopez, C.X., Bastin, L., Foody, G.M., Rocchini, D. (2016). A virtual species set for robust and reproducible Species Distribution Modelling tests. Data in Brief, 7: 476-479. doi: http://dx.doi.org/10.1016/j.dib.2016.02.058

Barrier1 Systems is showcasing a lineup of crash-rated barriers at ISC West 2024 in Booth 4109.

In recent years, open standards have been instrumental in helping manufacturers innovate, reduce costs and improve quality in a highly competitive international marketplace.

By combining thermal analytics, geospatial capabilities and AI-enabled solutions, integrators can now achieve real-time, proactive and reliable outdoor security.

Adelaide, Australia — Employers with stronger psychosocial safety climates experience fewer days lost to work-related ailments, as well as lower injury costs, results of a recent study out of Australia suggest.

By expanding its capabilities to address the growing consumer interest in functional beverages, the company is poised to offer partners and customers the opportunity to meet consumer needs and expectations while embracing current food and beverage trends and advancements in the market.

The shift toward automation has radically changed the infrastructure requirements for food manufacturers.

During the automatic processing of crystallographic diffraction experiments, beamstop shadows are often unaccounted for or only partially masked. As a result of this, outlier reflection intensities are integrated, which is a known issue. Traditional statistical diagnostics have only limited effectiveness in identifying these outliers, here termed Not-Excluded-unMasked-Outliers (NEMOs). The diagnostic tool AUSPEX allows visual inspection of NEMOs, where they form a typical pattern: clusters at the low-resolution end of the AUSPEX plots of intensities or amplitudes versus resolution. To automate NEMO detection, a new algorithm was developed by combining data statistics with a density-based clustering method. This approach demonstrates a promising performance in detecting NEMOs in merged data sets without disrupting existing data-reduction pipelines. Re-refinement results indicate that excluding the identified NEMOs can effectively enhance the quality of subsequent structure-determination steps. This method offers a prospective automated means to assess the efficacy of a beamstop mask, as well as highlighting the potential of modern pattern-recognition techniques for automating outlier exclusion during data processing, facilitating future adaptation to evolving experimental strategies.

Serial crystallography experiments at synchrotron and X-ray free-electron laser (XFEL) sources are producing crystallographic data sets of ever-increasing volume. While these experiments have large data sets and high-frame-rate detectors (around 3520 frames per second), only a small percentage of the data are useful for downstream analysis. Thus, an efficient and real-time data classification pipeline is essential to differentiate reliably between useful and non-useful images, typically known as `hit' and `miss', respectively, and keep only hit images on disk for further analysis such as peak finding and indexing. While feature-point extraction is a key component of modern approaches to image classification, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. This paper proposes a pipeline to categorize the data, consisting of a real-time feature extraction algorithm called modified and parallelized FAST (MP-FAST), an image descriptor and a machine learning classifier. For parallelizing the primary operations of the proposed pipeline, central processing units, graphics processing units and field-programmable gate arrays are implemented and their performances compared. Finally, MP-FAST-based image classification is evaluated using a multi-layer perceptron on various data sets, including both synthetic and experimental data. This approach demonstrates superior performance compared with other feature extractors and classifiers.

Silver Crown Royalties Inc. (SCRI:CBOE; SLCRF:OTCQX; QS0:FSE) announced record quarterly revenues in its financial results for the third quarter ending on September 30, 2024. Read more about the impressive growth in silver deliveries and how the company is strategically positioned for continued expansion.

Safe, effective antimicrobial medicines are essential to modern medical procedures and pandemic preparedness. A new National Academies report recommends a range of policy, regulatory, and financial actions to tackle antimicrobial resistance, spanning human, animal, and environmental health.

The company is among the biggest stock market winners of the generative AI boom, with its shares more than doubling in value this year.

The company will sample coated pretzels and mocktails at the event July 16–19 in Chicago.

New store conversions, openings and 35-year franchise renewals set up Signarama for remarkable success

Machine manufacturer in the USA has been providing equipment for trade schools for almost 50 years

Strategic Insights: PMMA Industry Outlook

SMAART Company's Q3 Success Paves the Way for Equity Financing, Attracting New Investors and Driving Growth

With solid sales performance, a steady stream of new locations, and expanding markets, the promotional products distributor positions itself for a remarkable 2024.

Sophia Antipolis, 9 July 2024

ETSI is excited to announce OpenCAPIF Release 1 is now available in the ETSI Labs.

OpenCAPIF develops a Common API Framework as defined by 3GPP and this new version introduces several improvements and new features to deliver a more robust, secure, and efficient API Management Platform. These advancements are developed in tight collaboration and incorporating feedback from a growing Research Ecosystem including SNS projects such as 6G-SANDBOX, FIDAL, IMAGINEB5G, SAFE6G, ORIGAMI, ENVELOPE and SUNRISE6G.

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Investments in regional transit service would create 13-times the return in value in household and travel times savings, according to new research made public today at the Chicago Transit Board of Directors’ monthly meeting.

One of the most critical performance factors for hiring teams is time to hire. Only 30% of organizations can fill a position within 30 days. The remaining candidates take anything from one to four months to get hired. Why should you try to shorten the hiring process? Taking too long to fill a ...

Shannon Selbert, co-founder of Soren and developer of Oban, and Parker Selbert, creator of the Oban background job framework, chief architect at dscout, and co-founder of Soren, speak with SE Radio host Gavin Henry about robust job processing in Elixir. They explore the reliability, consistency, and observability in relation to job processing, to understand how Oban, Elixir, and PostgreSQL deliver them.

The Selberts describe why Oban was created, its history, which parts of the Elixir ecosystem they use, and why this would not be possible without PostgreSQL and Elixir. They discuss the lessons learned in the 5 years since the first release, as well as use cases, job throughput, the hardest problem to solve so far, workers, queues, CRON, distributed architectures, retry algorithms, just-once methodologies, the reliability the beam brings, consistency across nodes, how PostgreSQL is vital, telemetry data, best use cases for Oban, and the most common issues that new users face. Brought to you by IEEE Computer Society and IEEE Software magazine.

New Appendix V - Provisional planning values for the fullband equipment impairment factor and the fullband packet loss robustness factor

Globally, a data breach costs an estimated €3m and yet less than a third of Irish companies are well prepared.

Read more: Only 28pc of Irish companies have ‘robust’ cybersecurity measures

[Daily Trust] The federal government has stressed the importance of robust personal data protection to prevent cybercrimes and foster trust.

Location: Electronic Resource- 

Weixian Deng
Dec 22, 2020; 0:RA120.002411v1-mcp.RA120.002411
Research

R. Greg Stacey
Nov 4, 2020; 0:RA120.002275v1-mcp.RA120.002275
Research

Insulin receptor substrate 2 (IRS2) is an essential adaptor that mediates signaling downstream of the insulin receptor and other receptor tyrosine kinases. Transduction through IRS2-dependent pathways is important for coordinating metabolic homeostasis, and dysregulation of IRS2 causes systemic insulin signaling defects. Despite the importance of maintaining proper IRS2 abundance, little is known about what factors mediate its protein stability. We conducted an unbiased proteomic screen to uncover novel substrates of the Anaphase Promoting Complex/Cyclosome (APC/C), a ubiquitin ligase that controls the abundance of key cell cycle regulators. We found that IRS2 levels are regulated by APC/C activity and that IRS2 is a direct APC/C target in G₁. Consistent with the APC/C's role in degrading cell cycle regulators, quantitative proteomic analysis of IRS2-null cells revealed a deficiency in proteins involved in cell cycle progression. We further show that cells lacking IRS2 display a weakened spindle assembly checkpoint in cells treated with microtubule inhibitors. Together, these findings reveal a new pathway for IRS2 turnover and indicate that IRS2 is a component of the cell cycle control system in addition to acting as an essential metabolic regulator.

Biological functions emerge from complex and dynamic networks of protein-protein interactions. Because these protein-protein interaction networks, or interactomes, represent pairwise connections within a hierarchically organized system, it is often useful to identify higher-order associations embedded within them, such as multi-member protein complexes. Graph-based clustering techniques are widely used to accomplish this goal, and dozens of field-specific and general clustering algorithms exist. However, interactomes can be prone to errors, especially when inferred from high-throughput biochemical assays. Therefore, robustness to network-level noise is an important criterion for any clustering algorithm that aims to generate robust, reproducible clusters. Here, we tested the robustness of a range of graph-based clustering algorithms in the presence of noise, including algorithms common across domains and those specific to protein networks. Strikingly, we found that all of the clustering algorithms tested here markedly amplified noise within the underlying protein interaction network. Randomly rewiring only 1% of network edges yielded more than a 50% change in clustering results, indicating that clustering markedly amplified network-level noise. Moreover, we found the impact of network noise on individual clusters was not uniform: some clusters were consistently robust to injected noise while others were not. To assist in assessing this, we developed the clust.perturb R package and Shiny web application to measure the reproducibility of clusters by randomly perturbing the network. We show that clust.perturb results are predictive of real-world cluster stability: poorly reproducible clusters as identified by clust.perturb are significantly less likely to be reclustered across experiments. We conclude that graph-based clustering amplifies noise in protein interaction networks, but quantifying the robustness of a cluster to network noise can separate stable protein complexes from spurious associations.

Deep proteome coverage in bottom-up proteomics requires peptide-level fractionation to simplify the complex peptide mixture before analysis by tandem mass spectrometry. By decreasing the number of co-eluting precursor peptide ions, fractionation effectively reduces the complexity of the sample leading to higher sample coverage and reduced bias towards high abundance precursors that are preferentially identified in data-dependent acquisition strategies. To achieve this goal, we report a bead-based off-line peptide fractionation method termed CIF or Carboxylate modified magnetic bead-based isopropanol gradient peptide fractionation. CIF is an extension of the SP3 (single-pot solid-phase-enhanced sample preparation) strategy and provides an effective but complementary approach to other commonly used fractionation methods including strong cation exchange (SCX) and reversed phase (RP)-based chromatography. We demonstrate that CIF is an effective offline separation strategy capable of increasing the depth of peptide analyte coverage both when used alone or as a second dimension of peptide fractionation in conjunction with high pH RP. These features make it ideally suited for a wide range of proteomic applications including the affinity purification of low abundance bait proteins.

I was literally confused to deployment testing services and testing scenarios, but thank to my one friend who advised me to use the computaris “top testing suite”. It was the...

As India is poised to see a surge in energy demand than any other country over the next decade owing to its sheer size and scale of rising demand from all sectors, the country's power transmission sector is set for significant growth due to ambitious renewable energy targets.