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Rage Against the Algorithm: the Risks of Overestimating Military Artificial Intelligence

27 August 2020

Yasmin Afina

Research Assistant, International Security Programme
Increasing dependency on artificial intelligence (AI) for military technologies is inevitable and efforts to develop these technologies to use in the battlefield is proceeding apace, however, developers and end-users must ensure the reliability of these technologies, writes Yasmin Afina.

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F-16 SimuSphere HD flight simulator at Link Simulation in Arlington, Texas, US. Photo: Getty Images.

AI holds the potential to replace humans for tactical tasks in military operations beyond current applications such as navigation assistance. For example, in the US, the Defense Advanced Research Projects Agency (DARPA) recently held the final round of its AlphaDogfight Trials where an algorithm controlling a simulated F-16 fighter was pitted against an Air Force pilot in virtual aerial combat. The algorithm won by 5-0. So what does this mean for the future of military operations?

The agency’s deputy director remarked that these tools are now ‘ready for weapons systems designers to be in the toolbox’. At first glance, the dogfight shows that an AI-enabled air combat would provide tremendous military advantage including the lack of survival instincts inherent to humans, the ability to consistently operate with high acceleration stress beyond the limitations of the human body and high targeting precision.

The outcome of these trials, however, does not mean that this technology is ready for deployment in the battlefield. In fact, an array of considerations must be taken into account prior to their deployment and use – namely the ability to adapt in real-life combat situations, physical limitations and legal compliance.

Testing environment versus real-life applications

First, as with all technologies, the performance of an algorithm in its testing environment is bound to differ from real-life applications such as in the case of cluster munitions. For instance, Google Health developed an algorithm to help with diabetic retinopathy screening. While the algorithm’s accuracy rate in the lab was over 90 per cent, it did not perform well out of the lab because the algorithm was used to high-quality scans in its training, it rejected more than a fifth of the real-life scans which were deemed as being below the quality threshold required. As a result, the process ended up being as time-consuming and costly – if not more so – than traditional screening.

Similarly, virtual environments akin to the AlphaDogfight Trials do not reflect the extent of risks, hazards and unpredictability of real-life combat. In the dogfight exercise, for example, the algorithm had full situational awareness and was repeatedly trained to the rules, parameters and limitations of its operating environment. But, in a real-life dynamic and battlefield, the list of variables is long and will inevitably fluctuate: visibility may be poor, extreme weather could affect operations and the performance of aircraft and the behaviour and actions of adversaries will be unpredictable.

Every single eventuality would need to be programmed in line with the commander’s intent in an ever-changing situation or it would drastically affect the performance of algorithms including in target identification and firing precision.

Hardware limitations

Another consideration relates to the limitations of the hardware that AI systems depend on. Algorithms depend on hardware to operate equipment such as sensors and computer systems – each of which are constrained by physical limitations. These can be targeted by an adversary, for example, through electronic interference to disrupt the functioning of the computer systems which the algorithms are operating from.

Hardware may also be affected involuntarily. For instance, a ‘pilotless’ aircraft controlled by an algorithm can indeed undergo higher accelerations, and thus, higher g-force than the human body can endure. However, the aircraft in itself is also subject to physical limitations such as acceleration limits beyond which parts of the aircraft, such as its sensors, may be severely damaged which in turn affects the algorithm’s performance and, ultimately, mission success. It is critical that these physical limitations are factored into the equation when deploying these machines especially when they so heavily rely on sensors.

Legal compliance

Another major, and perhaps the greatest, consideration relates to the ability to rely on machines for legal compliance. The DARPA dogfight exclusively focused on the algorithm’s ability to successfully control the aircraft and counter the adversary, however, nothing indicates its ability to ensure that strikes remain within the boundaries of the law.

In an armed conflict, the deployment and use of such systems in the battlefield are not exempt from international humanitarian law (IHL) and most notably its customary principles of distinction, proportionality and precautions in attack. It would need to be able to differentiate between civilians, combatants and military objectives, calculate whether its attacks will be proportionate against the set military objective and live collateral damage estimates and take the necessary precautions to ensure the attacks remain within the boundaries of the law – including the ability to abort if necessary. This would also require the machine to have the ability to stay within the rules of engagement for that particular operation.

It is therefore critical to incorporate IHL considerations from the conception and throughout the development and testing phases of algorithms to ensure the machines are sufficiently reliable for legal compliance purposes.

It is also important that developers address the 'black box' issue whereby the algorithm’s calculations are so complex that it is impossible for humans to understand how it came to its results. It is not only necessary to address the algorithm’s opacity to improve the algorithm’s performance over time, it is also key for accountability and investigation purposes in cases of incidents and suspected violations of applicable laws.

Reliability, testing and experimentation

Algorithms are becoming increasingly powerful and there is no doubt that they will confer tremendous advantages to the military. Over-hype, however, must be avoided at the expense of the machine’s reliability on the technical front as well as for legal compliance purposes.

The testing and experimentation phases are key during which developers will have the ability to fine-tune the algorithms. Developers must, therefore, be held accountable for ensuring the reliability of machines by incorporating considerations pertaining to performance and accuracy, hardware limitations as well as legal compliance. This could help prevent incidents in real life that result from overestimating of the capabilities of AI in military operations. 




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COP27: Navigating a difficult road to Sharm El-Sheikh

COP27: Navigating a difficult road to Sharm El-Sheikh Expert comment NCapeling 6 July 2022

Against a backdrop of rising urgency, COP27 in Egypt will bring all aspects of climate action into the spotlight – but especially the role of the host country.

As COP26 drew to a close in Glasgow, Egyptian officials announced their priorities for COP27, emphasizing climate finance and climate adaptation – a new approach given previous COPs mainly focused on mitigation, reducing emissions to limit climate damage.

This was followed by the COP27 presidency outlining its vision at MENA Climate Week 2022 to achieve ‘substantive and equal progress’ on all aspects of the negotiations, and Egypt emphasizing its intention to focus on implementing existing carbon reduction targets rather than pushing for further carbon cuts.

Egypt argues it is hosting COP27 on behalf of African nations and that, while it is promoting the interests of the developing world, it will be an impartial arbiter. However it is also useful to consider its priorities from the Egyptian government’s perspective.

Agenda drivers

Egypt has long prioritized climate finance and adaptation because it remains in need of technical and financial support to adapt, especially in agriculture and tourism.

It plans to expand its access to climate funding and investment, an area in which Egypt has been relatively successful as it currently receives 27 per cent of all multilateral climate finance in the MENA region and has issued the region’s first sovereign green bonds.

With public debt currently 94 per cent of GDP, Egyptian officials have also called for debt relief for Egypt and other developing countries.

Egypt’s Climate Change Strategy reflects this approach, aiming to enhance Egypt’s rank on the Climate Change Performance Index in order to ‘attract more investments and acquire more climate funding’.

Not pushing for more emission reductions at this critical moment risks derailing global decarbonization momentum and undermining global climate action

Limiting the mitigation scope and the focus on finance also echoes Egypt’s own reluctance to make carbon reduction commitments. The Egyptian nationally determined contribution (NDC) – its 2030 pledge under the Paris Agreement – does not include any quantifiable emission reduction targets.

Egypt is one of only a few countries which failed to submit an updated NDC in 2021 and its upcoming update will not include an economy-wide carbon reduction target.

Egypt has also never published a long-term strategy and has no decarbonization plans despite independent estimates it should cut rising emissions by one-quarter by 2030, and by two-thirds by 2050 to be aligned with the Paris Agreement. This partly explains why observers rate Egypt’s climate action as highly insufficient.

Furthermore, Egypt’s championing of ‘moving from pledges to implementation’ without having quantifiable carbon reduction pledges of its own effectively exempts it from both pledging and implementation.

As a developing country, Egypt’s negotiating position is supported by UNFCCC provisions which recognize differentiated responsibilities and respective capabilities of nations.

Its proposal to focus COP27 on the implementation of climate action and finance pledges is important in consolidating progress. But not pushing for more emission reductions at this critical moment risks derailing global decarbonization momentum and undermining global climate action.

According to optimistic estimates, if current climate pledges were implemented the world would still remain on track for 2°C of warming by the end of the century, with far worse impacts than if warming was curbed at 1.5°C.

Under a 2°C scenario, 37 per cent of the global population could regularly be exposed to extreme heat waves compared to 14 per cent in a 1.5°C warmer world, with developing countries expected to be worst-affected.

A 2°C trajectory also runs the risk of tipping points such as the melting of ice sheets in Antarctica and Greenland, triggering runaway climate change. Time to change the warming trajectory is running out as the latest IPCC assessment warns the window of opportunity is now ‘brief and rapidly closing’, and the UN Secretary General recently called for faster carbon cuts by the end of 2022 to avoid a ‘climate catastrophe’.

A different energy transition

Egypt opted not to join any of the voluntary sectoral coalitions at COP26 on reducing methane, clean energy transition, transition to zero-emissions vehicles, or moving beyond oil and gas.

This position is explained by its growing role as an exporter and advocate for fossil gas in the energy transition. Egypt is the second-largest producer of natural gas in Africa and is emerging as a fossil gas hub for the eastern Mediterranean, which is shaping its domestic energy policy.

Egypt is open to dialogue – not just on refining the COP27 agenda but also on reviewing its own climate priorities and leveraging its energy sector for a more ambitious transition

Its 59GW electricity generation capacity is almost double the peak demand and is dominated by gas-powered electricity generation, which currently represents 42 per cent of all Africa’s gas generation.

Egypt’s climate policy is also shaped by fossil gas, and its national Climate Change Strategy encourages the expansion of gas use by promoting a transition to compressed natural gas for vehicles, the expansion of its domestic natural gas network – despite having universal access to electricity – and shifting to a gas-fuelled shipping sector.

Egypt also voiced support for other African countries to extract and deploy fossil gas and oil resources, making it one of the protagonists of the ‘great fossil gas pushback’. These advocates defend the right of developing countries to deploy fossil gas as a ‘transition fuel’ and champion its necessity to solve energy poverty.

But their position is not shared by all African and developing countries, and is rejected by some civil society groups, who argue it risks locking in greenhouse gases and local emissions for decades as well as delaying future development of low carbon energy systems.

Egypt’s huge spare generation capacity has contributed to a slowdown in renewable energy projects over the past two years. With renewables representing just 6GW, Egypt is expected to miss its renewable energy target for 2022, set at 20 per cent of generating capacity.

Engaging Egypt better

But these positions are more malleable than they seem, and Egypt is open to dialogue – not just on refining the COP27 agenda but also on reviewing its own climate priorities and leveraging its energy sector for a more ambitious transition.




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MIRD Pamphlet No. 31: MIRDcell V4--Artificial Intelligence Tools to Formulate Optimized Radiopharmaceutical Cocktails for Therapy

Visual Abstract




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Modeling PET Data Acquired During Nonsteady Conditions: What If Brain Conditions Change During the Scan?

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.




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International Metabolic Prognostic Index Is Superior to Other Metabolic Tumor Volume-Based Prognostication Methods in a Real-Life Cohort of Diffuse Large B-Cell Lymphoma

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Pacific Rim timeline: Information for defenders from a braid of interlocking attack campaigns

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Digital Detritus: The engine of Pacific Rim and a call to the industry for action

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Pacific Rim: Learning to eat soup with a knife

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Pacific Rim: What’s it to you?

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From the frontlines: Our CISO’s view of Pacific Rim

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"Questioning the Quantifiable: Are We Measuring What Matters in Heart Failure Care?"




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Novel Proteomic Profiling of Epididymal Extracellular Vesicles in the Domestic Cat Reveals Proteins Related to Sequential Sperm Maturation with Differences Observed between Normospermic and Teratospermic Individuals

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PTM-Shepherd: analysis and summarization of post-translational and chemical modifications from open search results

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Protein modification characteristics of the malaria parasite Plasmodium falciparum and the infected erythrocytes

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Plasma proteomic data can contain personally identifiable, sensitive information and incidental findings

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Pluripotency of embryonic stem cells lacking clathrin-mediated endocytosis cannot be rescued by restoring cellular stiffness [Molecular Biophysics]

Mouse embryonic stem cells (mESCs) display unique mechanical properties, including low cellular stiffness in contrast to differentiated cells, which are stiffer. We have previously shown that mESCs lacking the clathrin heavy chain (Cltc), an essential component for clathrin-mediated endocytosis (CME), display a loss of pluripotency and an enhanced expression of differentiation markers. However, it is not known whether physical properties such as cellular stiffness also change upon loss of Cltc, similar to what is seen in differentiated cells, and if so, how these altered properties specifically impact pluripotency. Using atomic force microscopy (AFM), we demonstrate that mESCs lacking Cltc display higher Young's modulus, indicative of greater cellular stiffness, compared with WT mESCs. The increase in stiffness was accompanied by the presence of actin stress fibers and accumulation of the inactive, phosphorylated, actin-binding protein cofilin. Treatment of Cltc knockdown mESCs with actin polymerization inhibitors resulted in a decrease in the Young's modulus to values similar to those obtained with WT mESCs. However, a rescue in the expression profile of pluripotency factors was not obtained. Additionally, whereas WT mouse embryonic fibroblasts could be reprogrammed to a state of pluripotency, this was inhibited in the absence of Cltc. This indicates that the presence of active CME is essential for the pluripotency of embryonic stem cells. Additionally, whereas physical properties may serve as a simple readout of the cellular state, they may not always faithfully recapitulate the underlying molecular fate.




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Site-specific contacts enable distinct modes of TRPV1 regulation by the potassium channel Kv{beta}1 subunit [Molecular Biophysics]

Transient receptor potential vanilloid 1 (TRPV1) channel is a multimodal receptor that is responsible for nociceptive, thermal, and mechanical sensations. However, which biomolecular partners specifically interact with TRPV1 remains to be elucidated. Here, we used cDNA library screening of genes from mouse dorsal root ganglia combined with patch-clamp electrophysiology to identify the voltage-gated potassium channel auxiliary subunit Kvβ1 physically interacting with TRPV1 channel and regulating its function. The interaction was validated in situ using endogenous dorsal root ganglia neurons, as well as a recombinant expression model in HEK 293T cells. The presence of Kvβ1 enhanced the expression stability of TRPV1 channels on the plasma membrane and the nociceptive current density. Surprisingly, Kvβ1 interaction also shifted the temperature threshold for TRPV1 thermal activation. Using site-specific mapping, we further revealed that Kvβ1 interacted with the membrane-distal domain and membrane-proximal domain of TRPV1 to regulate its membrane expression and temperature-activation threshold, respectively. Our data therefore suggest that Kvβ1 is a key element in the TRPV1 signaling complex and exerts dual regulatory effects in a site-specific manner.




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AggreCount: an unbiased image analysis tool for identifying and quantifying cellular aggregates in a spatially defined manner [Methods and Resources]

Protein quality control is maintained by a number of integrated cellular pathways that monitor the folding and functionality of the cellular proteome. Defects in these pathways lead to the accumulation of misfolded or faulty proteins that may become insoluble and aggregate over time. Protein aggregates significantly contribute to the development of a number of human diseases such as amyotrophic lateral sclerosis, Huntington's disease, and Alzheimer's disease. In vitro, imaging-based, cellular studies have defined key biomolecular components that recognize and clear aggregates; however, no unifying method is available to quantify cellular aggregates, limiting our ability to reproducibly and accurately quantify these structures. Here we describe an ImageJ macro called AggreCount to identify and measure protein aggregates in cells. AggreCount is designed to be intuitive, easy to use, and customizable for different types of aggregates observed in cells. Minimal experience in coding is required to utilize the script. Based on a user-defined image, AggreCount will report a number of metrics: (i) total number of cellular aggregates, (ii) percentage of cells with aggregates, (iii) aggregates per cell, (iv) area of aggregates, and (v) localization of aggregates (cytosol, perinuclear, or nuclear). A data table of aggregate information on a per cell basis, as well as a summary table, is provided for further data analysis. We demonstrate the versatility of AggreCount by analyzing a number of different cellular aggregates including aggresomes, stress granules, and inclusion bodies caused by huntingtin polyglutamine expansion.




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AMPK{beta}1 and AMPK{beta}2 define an isoform-specific gene signature in human pluripotent stem cells, differentially mediating cardiac lineage specification [Cell Biology]

AMP-activated protein kinase (AMPK) is a key regulator of energy metabolism that phosphorylates a wide range of proteins to maintain cellular homeostasis. AMPK consists of three subunits: α, β, and γ. AMPKα and β are encoded by two genes, the γ subunit by three genes, all of which are expressed in a tissue-specific manner. It is not fully understood, whether individual isoforms have different functions. Using RNA-Seq technology, we provide evidence that the loss of AMPKβ1 and AMPKβ2 lead to different gene expression profiles in human induced pluripotent stem cells (hiPSCs), indicating isoform-specific function. The knockout of AMPKβ2 was associated with a higher number of differentially regulated genes than the deletion of AMPKβ1, suggesting that AMPKβ2 has a more comprehensive impact on the transcriptome. Bioinformatics analysis identified cell differentiation as one biological function being specifically associated with AMPKβ2. Correspondingly, the two isoforms differentially affected lineage decision toward a cardiac cell fate. Although the lack of PRKAB1 impacted differentiation into cardiomyocytes only at late stages of cardiac maturation, the availability of PRKAB2 was indispensable for mesoderm specification as shown by gene expression analysis and histochemical staining for cardiac lineage markers such as cTnT, GATA4, and NKX2.5. Ultimately, the lack of AMPKβ1 impairs, whereas deficiency of AMPKβ2 abrogates differentiation into cardiomyocytes. Finally, we demonstrate that AMPK affects cellular physiology by engaging in the regulation of hiPSC transcription in an isoform-specific manner, providing the basis for further investigations elucidating the role of dedicated AMPK subunits in the modulation of gene expression.




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Visualizing, quantifying, and manipulating mitochondrial DNA in vivo [Methods and Resources]

Mitochondrial DNA (mtDNA) encodes proteins and RNAs that support the functions of mitochondria and thereby numerous physiological processes. Mutations of mtDNA can cause mitochondrial diseases and are implicated in aging. The mtDNA within cells is organized into nucleoids within the mitochondrial matrix, but how mtDNA nucleoids are formed and regulated within cells remains incompletely resolved. Visualization of mtDNA within cells is a powerful means by which mechanistic insight can be gained. Manipulation of the amount and sequence of mtDNA within cells is important experimentally and for developing therapeutic interventions to treat mitochondrial disease. This review details recent developments and opportunities for improvements in the experimental tools and techniques that can be used to visualize, quantify, and manipulate the properties of mtDNA within cells.




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PTPN2 regulates the activation of KRAS and plays a critical role in proliferation and survival of KRAS-driven cancer cells [Signal Transduction]

RAS genes are the most commonly mutated in human cancers and play critical roles in tumor initiation, progression, and drug resistance. Identification of targets that block RAS signaling is pivotal to develop therapies for RAS-related cancer. As RAS translocation to the plasma membrane (PM) is essential for its effective signal transduction, we devised a high-content screening assay to search for genes regulating KRAS membrane association. We found that the tyrosine phosphatase PTPN2 regulates the plasma membrane localization of KRAS. Knockdown of PTPN2 reduced the proliferation and promoted apoptosis in KRAS-dependent cancer cells, but not in KRAS-independent cells. Mechanistically, PTPN2 negatively regulates tyrosine phosphorylation of KRAS, which, in turn, affects the activation KRAS and its downstream signaling. Consistently, analysis of the TCGA database demonstrates that high expression of PTPN2 is significantly associated with poor prognosis of patients with KRAS-mutant pancreatic adenocarcinoma. These results indicate that PTPN2 is a key regulator of KRAS and may serve as a new target for therapy of KRAS-driven cancer.




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A kinetic dissection of the fast and superprocessive kinesin-3 KIF1A reveals a predominant one-head-bound state during its chemomechanical cycle [Molecular Biophysics]

The kinesin-3 family contains the fastest and most processive motors of the three neuronal transport kinesin families, yet the sequence of states and rates of kinetic transitions that comprise the chemomechanical cycle and give rise to their unique properties are poorly understood. We used stopped-flow fluorescence spectroscopy and single-molecule motility assays to delineate the chemomechanical cycle of the kinesin-3, KIF1A. Our bacterially expressed KIF1A construct, dimerized via a kinesin-1 coiled-coil, exhibits fast velocity and superprocessivity behavior similar to WT KIF1A. We established that the KIF1A forward step is triggered by hydrolysis of ATP and not by ATP binding, meaning that KIF1A follows the same chemomechanical cycle as established for kinesin-1 and -2. The ATP-triggered half-site release rate of KIF1A was similar to the stepping rate, indicating that during stepping, rear-head detachment is an order of magnitude faster than in kinesin-1 and kinesin-2. Thus, KIF1A spends the majority of its hydrolysis cycle in a one-head-bound state. Both the ADP off-rate and the ATP on-rate at physiological ATP concentration were fast, eliminating these steps as possible rate-limiting transitions. Based on the measured run length and the relatively slow off-rate in ADP, we conclude that attachment of the tethered head is the rate-limiting transition in the KIF1A stepping cycle. Thus, KIF1A's activity can be explained by a fast rear-head detachment rate, a rate-limiting step of tethered-head attachment that follows ATP hydrolysis, and a relatively strong electrostatic interaction with the microtubule in the weakly bound post-hydrolysis state.




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Nuclear translocation ability of Lipin differentially affects gene expression and survival in fed and fasting Drosophila

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LDL apheresis as an alternate method for plasma LPS purification in healthy volunteers and dyslipidemic and septic patients

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Identification of unusual phospholipids from bovine heart mitochondria by HPLC-MS/MS

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Mutation in the distal NPxY motif of LRP1 alleviates dietary cholesterol-induced dyslipidemia and tissue inflammation

Anja Jaeschke
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Update on LIPID MAPS classification, nomenclature, and shorthand notation for MS-derived lipid structures

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Problem Notes for SAS®9 - 66542: The initial loading of a rule set and a rule flow takes significantly longer in SAS Business Rules Manager 3.3 compared with release 3.2

In SAS Business Rules Manager 3.3, the initial loading of a rule set and a rule flow takes significantly longer than it does in release 3.2. When this problem happens, long time gaps are evident in the local




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Problem Notes for SAS®9 - 58465: SAS Life Science Analytics Framework 4.6 - Group membership removal fails with an exception for Process Flows that exist in the Recycle Bin

In SAS Life Science Analytics Framework 4.6, group membership removal fails with an exception if a user is set as assignee, a candidate, or a notification recipient in a user task for a Process Flow . The Process




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Problem Notes for SAS®9 - 66511: A Russian translation shows the same value for two different variables in the Define Value dialog box for the Reply node in SAS Customer Intelligence Studio

In SAS Customer Intelligence Studio,  when you add  Reply- node variable values in the Define Value dialog box, you might notice that two identically labeled data-grid variables are




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Problem Notes for SAS®9 - 66507: The “RegisterFontTask" install task fails during out-of-the-box, add-on, or upgrade-in-place deployments if Hot Fix D7G004 is applied

The SAS 9.4M4 (TS1M4) Hot Fix D7G004 for ODS Templates installs national language support (NLS) content regardless of whether the languages were installed during the initial deployment. Having sparse