Securing in-memory processors against Row Hammering Attacks

Modern applications on general purpose processors require both rapid and power-efficient computing and memory components. As applications continue to improve, the demand for high speed computation, fast-access memory, and a secure platform increases. Traditional Von Neumann Architectures split the computing and memory units, causing both latency and high power-consumption issues; henceforth, a hybrid memory processing system is proposed, known as in-memory processing. In-memory processing alleviates the delay of computation and minimizes power-consumption; such improvements saw a 14x speedup improvement, 87\% fewer power consumption, and appropriate linear scalability versus performance. Several applications of in-memory processing include data-driven applications such as Artificial Intelligence (AI), Convolutional and Deep Neural Networks (CNNs/DNNs). However, processing-in-memory can also suffer from a security and reliability issue known as the Row Hammer Security Bug; this security exploit flips bits within memory without access, leading to error injection, system crashes, privilege separation, and total hijack of a system; the novel Row Hammer security bug can negatively impact the accuracies of CNNs and DNNs via flipping the bits of stored weight values without direct access. Weights of neural networks are stored in a variety of data patterns, resulting in either a solid (all 1s or all 0s), checkered (alternating 1s and 0s in both rows and columns), row-stripe (alternating 1s and 0s in rows), or column-striped (alternating 1s and 0s in columns) manner; the row-stripe data pattern exhibits the largest likelihood of a Row Hammer attack, resulting in the accuracies of neural networks dropping over 30\%. A row-stripe avoidance coding scheme is proposed to reduce the probability of the Row Hammer Attack occurring within neural networks. The coding scheme encodes the binary portion of a weight in a CNN or DNN to reduce the chance of row-stripe data patterns, overall reducing the likelihood of a Row Hammer attack occurring while improving the overall security of the in-memory processing system

Genetic Interaction between Mfrp and Adipor1 Mutations Affect Retinal Disease Phenotypes

Adipor1tm1Dgen and Mfrprd6 mutant mice share similar eye disease characteristics. Previously, studies established a functional relationship of ADIPOR1 and MFRP proteins in maintaining retinal lipidome homeostasis and visual function. However, the independent and/or interactive contribution of both genes to similar disease phenotypes, including fundus spots, decreased axial length, and photoreceptor degeneration has yet to be examined. We performed a gene-interaction study where homozygous Adipor1tm1Dgen and Mfrprd6 mice were bred together and the resulting doubly heterozygous F1 offspring were intercrossed to produce 210 F2 progeny. Four-month-old mice from all nine genotypic combinations obtained in the F2 generation were assessed for white spots by fundus photo documentation, for axial length by caliper measurements, and for photoreceptor degeneration by histology. Two-way factorial ANOVA was performed to study individual as well as gene interaction effects on each phenotype. Here, we report the first observation of reduced axial length in Adipor1tmlDgen homozygotes. We show that while Adipor1 and Mfrp interact to affect spotting and degeneration, they act independently to control axial length, highlighting the complex functional association between these two genes. Further examination of the molecular basis of this interaction may help in uncovering mechanisms by which these genes perturb ocular homeostasis

Risk Classification of Bladder Cancer by Gene Expression and Molecular Subtype

This study evaluated a panel including the molecular taxonomy subtype and the expression of 27 genes as a diagnostic tool to stratify bladder cancer patients at risk of aggressive behavior, using a well-characterized series of non-muscle invasive bladder cancer (NMIBC) as well as muscle-invasive bladder cancer (MIBC). The study was conducted using the novel NanoString nCounter gene expression analysis. This technology allowed us to identify the molecular subtype and to analyze the gene expression of 27 bladder-cancer-related genes selected through a recent literature search. The differential gene expression was correlated with clinicopathological variables, such as the molecular subtypes (luminal, basal, null/double negative), histological subtype (conventional urothelial carcinoma, or carcinoma with variant histology), clinical subtype (NMIBC and MIBC), tumor stage category (Ta, T1, and T2–4), tumor grade, PD-L1 expression (high vs. low expression), and clinical risk categories (low, intermediate, high and very high). The multivariate analysis of the 19 genes significant for cancer-specific survival in our cohort study series identified TP53 (p = 0.0001), CCND1 (p = 0.0001), MKI67 (p < 0.0001), and molecular subtype (p = 0.005) as independent predictors. A scoring system based on the molecular subtype and the gene expression signature of TP53, CCND1, or MKI67 was used for risk assessment. A score ranging from 0 (best prognosis) to 7 (worst prognosis) was obtained and used to stratify our patients into two (low [score 0–2] vs. high [score 3–7], model A) or three (low [score 0–2] vs. intermediate [score 3–4] vs. high [score 5–7], model B) risk categories with different survival characteristics. Mean cancer-specific survival was longer (122 + 2.7 months) in low-risk than intermediate-risk (79.4 + 9.4 months) or high-risk (6.2 + 0.9 months) categories (p < 0.0001; model A); and was longer (122 + 2.7 months) in low-risk than high-risk (58 + 8.3 months) (p < 0.0001; model B). In conclusion, the molecular risk assessment model, as reported here, might be used better to select the appropriate management for patients with bladder cancer

The Modeling of Anisotropic Fuselage Lining Material

In this paper a theoretical model that can account for the effect of lining anisotropy on sound transmission through fuselage structures is developed. The model allows for anisotropic flow resistivity, tortuosity and elastic moduli. Implicit to the theory is a characteristic dispersion relation of sixth order that yields the allowed wave numbers for wave propagation in anisotropic elastic porous media. In addition, explicit expressions for field variables such as displacements and stresses appropriate for anisotropic foams are derived. Predictions of random incidence sound transmission loss for double panels with anisotropic linings have been performed. To verify the prediction, the theoretical results have been compared with random incidence transmission loss measurements

HIF-transcribed p53 chaperones HIF-1α

Chronic hypoxia is associated with a variety of physiological conditions such as rheumatoid arthritis, ischemia/reperfusion injury, stroke, diabetic vasculopathy, epilepsy and cancer. At the molecular level, hypoxia manifests its effects via activation of HIF-dependent transcription. On the other hand, an important transcription factor p53, which controls a myriad of biological functions, is rendered transcriptionally inactive under hypoxic conditions. p53 and HIF-1α are known to share a mysterious relationship and play an ambiguous role in the regulation of hypoxia-induced cellular changes. Here we demonstrate a novel pathway where HIF-1α transcriptionally upregulates both WT and MT p53 by binding to five response elements in p53 promoter. In hypoxic cells, this HIF-1α-induced p53 is transcriptionally inefficient but is abundantly available for protein-protein interactions. Further, both WT and MT p53 proteins bind and chaperone HIF-1α to stabilize its binding at its downstream DNA response elements. This p53-induced chaperoning of HIF-1α increases synthesis of HIF-regulated genes and thus the efficiency of hypoxia-induced molecular changes. This basic biology finding has important implications not only in the design of anti-cancer strategies but also for other physiological conditions where hypoxia results in disease manifestation

Post-streptococcal glomerulonephritis is a strong risk factor for chronic kidney disease in later life

Although unusual in western countries and in Australia in general, post-streptococcal glomerulonephritis (PSGN) is still common in Australian Aboriginal children living in remote communities. Here, we evaluated whether episodes of acute PSGN increased the risk for chronic kidney disease in later life in 1519 residents of a remote Aboriginal community (85% of those age eligible), with high rates of renal and cardiovascular disease, who participated in a health screen over a 3-year period. Of these, 200 had had at least one episode of PSGN, with 27 having had multiple episodes, usually in childhood. High levels of albuminuria (albumin/creatinine ratio) with increasing age were confirmed. All PSGN episodes were associated with group A streptococcal skin infections, often related to scabies. In both genders, aged 10-39 years at screening, about one in five had such a history. Among them, PSGN (5 years or more earlier) was significantly associated with higher levels of albuminuria than those without. In women, aged 30-39 years, a history of PSGN was associated with a significantly higher frequency of estimated glomerular filtration rates < 60 ml/min. The adjusted odds ratios for an albumin/creatinine ratio over 34 g/mol (overt albuminuria) in males and females with a history of PSGN were 4.6 and 3.1, respectively, compared with those without a history. Thus, PSGN contributes to the very serious burden of chronic kidney disease in this community. Rigorous strategies to prevent scabies and Group A streptococcal infections will reduce this burden

Cascade PID controller optimization using bison algorithm

Meta-heuristic algorithms are reliable tools for modern optimization. Yet their amount is so immense that it is hard to pick just one to solve a specific problem. Therefore many researchers hold on known, approved algorithms. But is it always beneficial? In this paper, we use the meta-heuristics for the design of cascade PID controllers and compare the performance of the newly developed Bison Algorithm with well-known algorithms like the Differential Evolution, the Genetics Algorithm, the Particle Swarm Optimization, and the Cuckoo Search. Also, in the proposed approach, the controller parameters were encoded to increase the chance of reducing the controller structure, and thus facilitate the automatic selection of its configuration. The simulations were performed for three different control problems and checked whether the use of cascade structures could bring significant benefits in comparison to the use of classic PID controllers. © 2020, Springer Nature Switzerland AG