A new campaign has targeted the npm package repository with malicious JavaScript libraries that are designed to infect Roblox users with open-source stealer malware such as Skuld and Blank-Grabber. "This incident highlights the alarming ease with which threat actors can launch supply chain attacks by exploiting trust and human error within the open source ecosystem, and using readily available

Hisashi Kobayashi, whose steady leadership as dean guided Princeton's School of Engineering and Applied Science through a rapid expansion of programs and facilities in the late 1980s and early 1990s, died on March 9. He was 84.

Use the Secrets in Your Data Outreach Toolkit to organize screenings and events in your community about personal data privacy and security online.

Here are some tips and tricks pulled from Secrets in Your Data to help you stay safe online.

Practical tips for creating a strong password and keeping your data safe online.

7-minute video shows you how to filter and display data in a datagrid as part of your digital signage software presentations for display on any screen, anywhere. This feature is available in Repeat Signage Corporate or Media Wall editions and is ideal for corporate offices to help keep staff updated on relevant information

7-minute video shows how you can a single line of text from either a .txt file or a database, for example, displaying name of duty manager. The ability to display database information is available in the Corporate and Media Wall editions of Repeat Signage digital signage software. Ideal for displaying company information on any screen anywhere.

The spreadsheet control within Repeat Signage software allows you to display existing Microsoft Excel .xlsx files and allows you to use the built in editor to create spreadsheets within your presentations. You can also create and display spreadsheet graphs from your information. This gives you an easy way to display formatted information in grids and you also have the ability to insert pictures as well.

40% of AI data centers will face operational constraints due to power shortages by 2027 as AI drives unprecedented energy consumption, research firm Gartner said on Tuesday. Data center power requirements for AI-optimized servers are projected to reach 500 terawatt-hours annually by 2027, more than double 2023 levels, as companies rapidly expand facilities to handle large language model training and implementation. The surge in power demand will outpace utility providers' ability to expand capacity, Gartner analyst Bob Johnson said, leading to higher electricity costs that will cascade through the AI industry. Some operators are already seeking direct agreements with power producers to secure guaranteed supply.

Read more of this story at Slashdot.

1. iPhone SE 4 expected to launch in March 2025, supply chain data suggests  Business Standard
2. iPhone SE4 is likely to launch soon and here are 5 big upgrades we are expecting  India Today
3. Apple iPhone SE 4 to launch next year, likely to become the cheapest iPhone to support Apple Intelligence...  Moneycontrol
4. iPhone SE 4 may spell trouble for iPhone 16 and premium Android phones, here’s why  Hindustan Times
5. iPhone SE 4 Camera Production to Begin Soon Ahead of Anticipated Debut in March 2025: Report  Gadgets 360

California's San Francisco Bay Area is still solidly blue — but less than it used to be.

Bond yields spiked aggressively as investors awaited Wednesday's inflation data for October.

A tech recruiting firm left a database unsecured that exposed emails, passport numbers and partial SSNs of job seekers, a security researcher says.

I have a close circle of clued-on/tech savvy friends whose views I take seriously. For the last few weeks, one of these friends has been sending me emails extolling the merits of something called IOTA – which calls itself as the next generation Blockchain.  At first, I thought of IOTA as yet another cryptocurrency. A [...]

  What if you could learn AI and Data Science based on knowledge you already know? You have an opportunity to accelerate your learning of AI in a unique way through this limited, early bird offer Here is a simple observation: The mathematical foundations of Data Science rest on four elements i.e. Linear Algebra, Probability [...]

The Internet Archive, an online repository of web pages, was offline Thursday after its founder confirmed a major cyberattack that exposed the data of millions of users and left the site defaced.

Google is investing in the development of the next generation of nuclear power, backing a company that’s building small modular reactors and agreeing to purchase energy once the sites start supplying US grids.

The South African Artificial Intelligence Association wants LinkedIn to be investigated, as it claims the social networking platforms new data use practice violates local personal information protection law.

Modern organizations regard data as a strategic asset that drives efficiency, enhances decision making, and creates new value for customers. Across the organization—product management, marketing, operations, finance, and more—teams are overflowing with ideas on how data can elevate the business. To bring these ideas to life, companies are eagerly hiring data scientists for their technical […]

This morning we awoke to one story dominating the tech news landscape: OpenAI is “expanding into search,” launching SearchGPT, a prototype that appears to be a direct competitor to Google (and Bing and Perplexity, not that they really matter). But despite the voluminous coverage, my initial take is that once the hype cycle passes – … Continue reading "What’s SearchGPT Really About? Moving Past the Training Data Dilemma."

What is the future of cross-border data flows? 16 September 2024 — 6:00PM TO 7:00PM Anonymous (not verified) 15 August 2024 Chatham House and Online

Navigating long-standing tensions and newfound difficulties for unlocking shared prosperity among modern, digital economies.

Cross-border data flows can unlock shared prosperity among digital economies, advance international security, and address cybercrime and global crises. But ensuring the free flow of data across borders involves navigating complex regulatory, security, trust, political, and technical challenges. Developing effective frameworks and agreements to support data flows is a significant undertaking.

Recent bilateral and multilateral agreements and initiatives have advanced data-sharing, respecting the right to privacy and upholding notions of sovereignty. This has contributed to clearer rules and (potentially) better solutions such as the OECD declaration on government access to data held by companies. Further progress, supportive of public safety and national security, is on the horizon, like G7 support for data free flow with trust and industry-led, trusted cloud principles on protecting human rights and competitiveness.

More work is needed to operationalize commitments and advance ongoing negotiations, like US–EU negotiations on e-evidence in criminal proceedings. This is key for ensuring ‘hard’ legal and regulatory mechanisms complement OECD principles. Stakeholders from law enforcement, national security, data protection and industry must confront tensions between sovereign prerogatives and cooperation. They must also overcome traditional silos between law enforcement and national security work. On the horizon are newfound challenges (for example, in harmonizing legal frameworks and responding to advances in technology). All the while, stakeholders must work together to promote economic interests, data protection, privacy and cybersecurity.

This expert panel discusses the future of cross-border data-sharing, raising questions including:

• What value does cross-border data-sharing bring and where are its current ‘pain points’?
• To enable data free flows, how should principles complement ‘hard’ legal and regulatory mechanisms?
• Beyond states, law enforcement, major industry players and international organizations, what roles should SMEs, the technical community and civil society stakeholders play in shaping and operationalizing principles?
• Looking ahead, where is progress in data-sharing principles and arrangements expected or possible?

A drinks reception follows the event.

This event is supported by Microsoft as part of a project on data sharing. The project has benefited greatly from the insights of a multi-stakeholder taskforce and concludes with an open-access special issue of the Journal of Cyber Policy.

M. Wang
Aug 1, 2012; 11:492-500
Technological Innovation and Resources

Roland Bruderer
May 1, 2015; 14:1400-1410
Research

Alexey I. Nesvizhskii
Oct 1, 2005; 4:1419-1440
Tutorial

Ludovic C. Gillet
Jun 1, 2012; 11:O111.016717-O111.016717
Research

Expert

Visualizing the Data: The Evolution of Trade Tensions in Metals and Minerals Markets 18 January 2018 — 4:30PM TO 6:00PM Anonymous (not verified) 19 December 2017 Chatham House, London

Over the past decade, producer countries such as South Africa, Zambia, Indonesia, the DRC and, most recently, Tanzania have restricted exports of unprocessed precious metals, copper, nickel, cobalt and other minerals in an attempt to support, or create, downstream processing industries and jobs or increase revenues. These moves have invariably created tensions with trading partners. Research suggests that export restrictions are not the best way to achieve such policy objectives and can instead harm the producer country’s economy and undermine the functioning of international metals and minerals.

Drawing on OECD and Chatham House research on resource trade, the speaker will present analysis and data visualizations exploring the drivers of past export restrictions and their political and economic impacts. They will also consider how the drivers of ‘resource nationalist measures’ are changing, whether and where export restrictions might present strategic and economic risks in the current context, and the extent to which producer and consumer governments and international governance mechanisms are prepared to address them.

Attendance at this event is by invitation only.

Angela Robinson explains the math behind the next generation of cryptographic algorithms. Whenever you log in to a website, send an email, or make an online purchase, you're counting on your data being sent securely, without hackers being able to crack the code. Our standard cryptographic systems hinge on mathematical problems that stump present-day computers, like finding the prime factors of a very large number. But in the coming decades, powerful quantum computers are expected to be able to rapidly solve some such problems, threatening the security of our online communications. To develop new methods that can withstand even the most sophisticated quantum computer, cryptographers are using a wide range of mathematical tools, many of which were originally developed without any real-life applications in mind.

Researchers use dynamic PET imaging with target-selective tracer molecules to probe molecular processes. Kinetic models have been developed to describe these processes. The models are typically fitted to the measured PET data with the assumption that the brain is in a steady-state condition for the duration of the scan. The end results are quantitative parameters that characterize the molecular processes. The most common kinetic modeling endpoints are estimates of volume of distribution or the binding potential of a tracer. If the steady state is violated during the scanning period, the standard kinetic models may not apply. To address this issue, time-variant kinetic models have been developed for the characterization of dynamic PET data acquired while significant changes (e.g., short-lived neurotransmitter changes) are occurring in brain processes. These models are intended to extract a transient signal from data. This work in the PET field dates back at least to the 1990s. As interest has grown in imaging nonsteady events, development and refinement of time-variant models has accelerated. These new models, which we classify as belonging to the first, second, or third generation according to their innovation, have used the latest progress in mathematics, image processing, artificial intelligence, and statistics to improve the sensitivity and performance of the earliest practical time-variant models to detect and describe nonsteady phenomena. This review provides a detailed overview of the history of time-variant models in PET. It puts key advancements in the field into historical and scientific context. The sum total of the methods is an ongoing attempt to better understand the nature and implications of neurotransmitter fluctuations and other brief neurochemical phenomena.

Zilu Ye
Dec 28, 2020; 0:R120.002204v1-mcp.R120.002204
Review

Philipp Emanuel Geyer
Dec 17, 2020; 0:RA120.002359v1-mcp.RA120.002359
Research

For data that is being loaded from a SAS Stored Process Server, an insertion process might fail to a MySQL database with a warning, as well as an error message that says "During insert: Incorrect datetime value…"

You encounter this issue when the table metadata matches the data source. In this scenario, no metadata update is required.

If you have configured more than one SAS Application Server, then SAS Visual Data Builder might unexpectedly use the wrong application server when you preview or schedule queries. This problem occurs even though you h

If the response variable is in the CLASS statement variable list before the class variables that also appear in the MODEL statement, and an OM-data-set is used, least squares means results for several of the statistical procedures are incorrect.

You might receive a Segmentation Violation when opening a database table in SAS. The SAS Log contains the error and traceback:

An error might occur when you use the SAS 9 BULKLOAD= and BULKEXTRACT= options load data to or extract data from HP Neoview on the HP Itanium platform. The problem occurs because Hewlett-Packard changed the name of one of

In SAS Merchandise Financial Planning, custom time frame-based data versions do not aggregate correctly when referenced in worksheets with standard hierarchy levels. The data does not aggregate correctly from l

If the OBSMARGINS= or OM= option is specified in an LSMEANS, LSMESTIMATE, or SLICE statement and a user-defined format is applied to any of the effect variables in the OM-data-set , PROC PLM incorrectly stops proce

When you use SAS/ACCESS Interface to PostgreSQL to query a Yellowbrick database, the SAS OBS= option is not generating a limit clause on the query that is passed to the database. Click the

When you publish a model to SAS Metadata Repository by using SAS Model Manager, the publishing process fails and the following error is generated: "The model model-name has a function of ';Transformation';, which is not supported for

Ion mobility brings an additional dimension of separation to LC–MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (~30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (~10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.

Mass spectrometry has become an indispensable tool for the characterization of glycosylation across biological systems. Our ability to generate rich fragmentation of glycopeptides has dramatically improved over the last decade yet our informatic approaches still lag behind. Although glycoproteomic informatics approaches using glycan databases have attracted considerable attention, database independent approaches have not. This has significantly limited high throughput studies of unusual or atypical glycosylation events such as those observed in bacteria. As such, computational approaches to examine bacterial glycosylation and identify chemically diverse glycans are desperately needed. Here we describe the use of wide-tolerance (up to 2000 Da) open searching as a means to rapidly examine bacterial glycoproteomes. We benchmarked this approach using N-linked glycopeptides of Campylobacter fetus subsp. fetus as well as O-linked glycopeptides of Acinetobacter baumannii and Burkholderia cenocepacia revealing glycopeptides modified with a range of glycans can be readily identified without defining the glycan masses before database searching. Using this approach, we demonstrate how wide tolerance searching can be used to compare glycan use across bacterial species by examining the glycoproteomes of eight Burkholderia species (B. pseudomallei; B. multivorans; B. dolosa; B. humptydooensis; B. ubonensis, B. anthina; B. diffusa; B. pseudomultivorans). Finally, we demonstrate how open searching enables the identification of low frequency glycoforms based on shared modified peptides sequences. Combined, these results show that open searching is a robust computational approach for the determination of glycan diversity within bacterial proteomes.

As the COVID-19 pandemic continues to spread, thousands of scientists around the globe have changed research direction to understand better how the virus works and to find out how it may be tackled. The number of manuscripts on preprint servers is soaring and peer-reviewed publications using MS-based proteomics are beginning to emerge. To facilitate proteomic research on SARS-CoV-2, the virus that causes COVID-19, this report presents deep-scale proteomes (10,000 proteins; >130,000 peptides) of common cell line models, notably Vero E6, Calu-3, Caco-2, and ACE2-A549 that characterize their protein expression profiles including viral entry factors such as ACE2 or TMPRSS2. Using the 9 kDa protein SRP9 and the breast cancer oncogene BRCA1 as examples, we show how the proteome expression data can be used to refine the annotation of protein-coding regions of the African green monkey and the Vero cell line genomes. Monitoring changes of the proteome on viral infection revealed widespread expression changes including transcriptional regulators, protease inhibitors, and proteins involved in innate immunity. Based on a library of 98 stable-isotope labeled synthetic peptides representing 11 SARS-CoV-2 proteins, we developed PRM (parallel reaction monitoring) assays for nano-flow and micro-flow LC–MS/MS. We assessed the merits of these PRM assays using supernatants of virus-infected Vero E6 cells and challenged the assays by analyzing two diagnostic cohorts of 24 (+30) SARS-CoV-2 positive and 28 (+9) negative cases. In light of the results obtained and including recent publications or manuscripts on preprint servers, we critically discuss the merits of MS-based proteomics for SARS-CoV-2 research and testing.

No abstract