Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing, Exploiting, Detecting and Preventing DMA Attacks in the Presence of an IOMMU

Malicious I/O devices might compromise the OS using DMAs. The OS therefore utilizes the IOMMU to map and unmap every target buffer right before and after its DMA is processed, thereby restricting DMAs to their designated locations. This usage model, however, is neither truly secure nor can it support multi-gigabit I/O operations. IOMMU provides protection at page granularity only, whereas DMA buffers can reside on the same page as other data leading to sub-page vulnerabilities, which make the system vulnerable to DMA attacks, in which I/O devices access and manipulate memory regions not intended for their use. We first categorize sub-page vulnerabilities into four categories, providing insight into the structure of DMA vulnerabilities. Then, to exploit these vulnerabilities, we identify a set of three vulnerability attributes that are sufficient to execute code injection attacks. We then build analysis tools that detect sub-page vulnerabilities and analyze the Linux kernel. We find that 72% of the device drivers expose sensitive callback pointers, which may be overwritten by a device to hijack kernel control flow. Aided by the tools’ output, we demonstrate novel code injection attacks on the Linux kernel we term compound attacks. Specifically, while all previously reported attacks are single-step, i.e., with the vulnerability attributes present in a single page, in compound attacks, the vulnerability attributes are initially incomplete. However, they can be attained by carefully exploiting standard OS behavior. In order to provide performant and secure I/O we propose that OSes utilize the IOMMU differently. Our new usage model restricts device access to a set of shadow DMA buffers that are never unmapped. The DMAed data is copied to/from these shadow buffers, thus providing subpage protection. Our key insight is that the cost of interacting with, and synchronizing access to the slow IOMMU hardware—required for zero-copy protection against devices—make copying preferable to zero-copying. We implement our model in Linux and evaluate it with standard networking benchmarks utilizing a 40 Gb/s NIC. We demonstrate that despite being more secure than the safest preexisting usage model, our approach provides up to 5× higher throughput. Additionally, whereas it is inherently less scalable than an IOMMU-less (unprotected) system, our approach incurs only 0%–25% performance degradation in comparison. Next, we observe that achieving protection at the DMA (un)map boundary is needlessly constraining, as devices must be prevented from changing the data only after the kernel reads it. So there is no real need to switch ownership of buffers between kernel and device at the DMA (un)mapping layer, as opposed to the approach taken by all existing IOMMU protection schemes. We thus eliminate the extra copy by (1) implementing a new allocator called DMAAware Malloc for Networking (DAMN), which (de)allocates packet buffers from a memory 1 Technion Computer Science Department Ph.D. Thesis PHD-2021-11 2021
Automated recognition of major depressive disorder from cardiovascular and respiratory physiological signals

Major Depressive Disorder (MDD) is a neurohormonal disorder that causes persistent negative thoughts, mood and feelings, often accompanied with suicidal ideation (SI). Current clinical diagnostic approaches are solely based on psychiatric interview questionnaires. Thus, a computational intelligence tool for the automated detection of MDD with and without suicidal ideation is presented in this study. Since MDD is proven to affect cardiovascular and respiratory systems, the aim of the study is to automatically identify the disorder severity in MDD patients using corresponding multi-modal physiological signals, including electrocardiogram (ECG), finger photoplethysmography (PPG) and respiratory signals (RSP). Data from 88 subjects were used in this study, out of which 25 were MDD patients without SI (MDDSI−), 18 MDD patients with SI (MDDSI+), and 45 normal subjects. Multi-modal physiological signals were acquired from each subject, including ECG, RSP, and PPG signals, and then pre-processed. Discrete wavelet transform (DWT) was applied to the signals, which were decomposed up to six levels, and then eleven nonlinear features were extracted. The features were ranked according to the analysis of variance test and Marginal Fisher Analysis was employed to reduce the feature set, after which the reduced features were ranked again to select the most discriminatory features. Support vector machine with polynomial radial basis function (SVM-RBF) as well as k-nearest neighbor (KNN) classifiers were used to classify the significant features. The performance of the classifiers was evaluated in a 10-fold cross validation scheme. The best performance achieved for the classification of MDDSI+ patients was up to 85.2%, by using selected features from the obtained multi-modal signals with SVM-RBF, while it was up to 96.6% for the detection of MDD patients against healthy subjects. This work is a step toward the utilization of automated tools in diagnostics and monitoring of MDD patients in a personalized and wearable healthcare system.
Recent progress in noble-metal-free electrocatalysts for alkaline oxygen evolution reaction

The practical application of splitting water to generate hydrogen is to a large extent hindered by an oxygen evolution reaction (OER) process. Electrocatalysts with low-cost, high activity, and durability are essential for the low kinetic threshold of the OER. Despite the high active performances of noble metal compound electrocatalysts like IrO2 and RuO2, they are heavily restricted by the high cost and scarcity of noble metal elements. In this context, noble-metal-free electrocatalysts have acquired increasing significance in recent years. So far, a broad spectrum of noble-metal-free electrocatalysts has been developed for improved OER performance. In this review, three types of electrolysis and some evaluation criteria are introduced, followed by recent progress in designing and synthesizing noble-metal-free alkaline OER electrocatalysts, with the classification of metal oxides/(oxy)hydroxides, carbon-based materials, and metal/carbon hybrids. Finally, perspectives are also provided on the future development of the alkaline OER on active sites and stability of electrocatalysts.
Antisense oligonucleotide is a promising intervention for liver diseases

As the body’s critical metabolic organ, the liver plays an essential role in maintaining proper body homeostasis. However, as people’s living standards have improved and the number of unhealthy lifestyles has increased, the liver has become overburdened. These have made liver disease one of the leading causes of death worldwide. Under the influence of adverse factors, liver disease progresses from simple steatosis to hepatitis, to liver fibrosis, and finally to cirrhosis and cancer, followed by increased mortality. Until now, there has been a lack of accepted effective treatments for liver disease. Based on current research, antisense oligonucleotide (ASO), as an alternative intervention for liver diseases, is expected to be an effective treatment due to its high efficiency, low toxicity, low dosage, strong specificity, and additional positive characteristics. In this review, we will first introduce the design, modification, delivery, and the mechanisms of ASO, and then summarize the application of ASO in liver disease treatment, including in non-alcoholic fatty liver disease (NAFLD), hepatitis, liver fibrosis, and liver cancer. Finally, we discuss challenges and perspectives on the transfer of ASO drugs into clinical use. This review provides a current and comprehensive understanding of the integrative and systematic functions of ASO for its use in liver disease.
Genomic adaptation of Ethiopian indigenous cattle to high altitude

The mountainous areas of Ethiopia represent one of the most extreme environmental challenges in Africa faced by humans and other inhabitants. Selection for high-altitude adaptation is expected to have imprinted the genomes of livestock living in these areas. Here we assess the genomic signatures of positive selection for high altitude adaptation in three cattle populations from the Ethiopian mountainous areas (Semien, Choke, and Bale mountains) compared to three Ethiopian lowland cattle populations (Afar, Ogaden, and Boran), using whole-genome resequencing and three genome scan approaches for signature of selection (iHS, XP-CLR, and PBS). We identified several candidate selection signature regions and several high-altitude adaptation genes. These include genes such as ITPR2, MB, and ARNT previously reported in the human population inhabiting the Ethiopian highlands. Furthermore, we present evidence of strong selection and high divergence between Ethiopian high- and low-altitude cattle populations at three new candidate genes (CLCA2, SLC26A2, and CBFA2T3), putatively linked to high-altitude adaptation in cattle. Our findings provide possible examples of convergent selection between cattle and humans as well as unique African cattle signature to the challenges of living in the Ethiopian mountainous regions.
Multi illumination color constancy based on multi-scale supervision and single-scale estimation cascade convolution neural network

Color constancy methods are generally based on a simplifying assumption that the spectral distribution of a light source is uniform across scenes. However, in reality, this assumption is often violated because of the presence of multiple light sources, that is, more than two illuminations. In this paper, we propose a unique cascade network of deep multi-scale supervision and single-scale estimation (CN-DMS4) to estimate multi-illumination. The network parameters are supervised and learned from coarse to fine in the training process and estimate only the final thinnest level illumination map in the illumination estimation process. Furthermore, to reduce the influence of the color channel on the Euclidean distance or the pixel-level angle error, a new loss function with a channel penalty term is designed to optimize the network parameters. Extensive experiments are conducted on single and multi-illumination benchmark datasets. In comparison with previous multi-illumination estimation methods, our proposed method displays a partial improvement in terms of quantitative data and visual effect, which provides the future research direction in end-to-end multi-illumination estimation.
TP53-related signature for predicting prognosis and tumor microenvironment characteristics in bladder cancer: A multi-omics study

Background: The tumor suppressor gene TP53 is frequently mutated or inactivated in bladder cancer (BLCA), which is implicated in the pathogenesis of tumor. However, the cellular mechanisms of TP53 mutations are complicated, yet well-defined, but their clinical prognostic value in the management of BLCA remains controversial. This study aimed to explore the role of TP53 mutation in regulating the tumor microenvironment (TME), elucidate the effects of TP53 activity on BLCA prognosis and immunotherapy response. Methods: A TP53-related signature based on TP53-induced and TP53-repressed genes was used to construct a TP53 activity-related score and classifier. The abundance of different immune cell types was determined using CIBERSORT to estimate immune cell infiltration. Moreover, the heterogeneity of the tumor immune microenvironment between the high and low TP53 score groups was further evaluated using single-cell mass cytometry (CyTOF) and imaging mass cytometry (IMC). Moreover, pathway enrichment analysis was performed to explore the differential biological functions between tumor epithelial cells with high and low TP53 activity scores. Finally, the receptor–ligand interactions between immune cells and tumor epithelial cells harboring distinct TP53 activity were analyzed by single-cell RNA-sequencing. Results: The TP53 activity-related gene signature differentiated well between TP53 functional retention and inactivation in BLCA. BLCA patients with low TP53 scores had worse survival prognosis, more TP53 mutations, higher grade, and stronger lymph node metastasis than those with high TP53 scores. Additionally, CyTOF and IMC analyses revealed that BLCA patients with low TP53 scores exhibited a potent immunosuppressive TME. Consistently, single-cell sequencing results showed that tumor epithelial cells with low TP53 scores were significantly associated with high cell proliferation and stemness abilities and strongly interacted with immunosuppressive receptor–ligand pairs. Conclusion: BLCA patients with low TP53 scores have a worse prognosis and a more immunosuppressive TME. This TP53 activity-related signature can serve as a potential prognostic signature for predicting the immune response, which may facilitate the development of new strategies for immunotherapy in BLCA.
High expression of B4GALT1 is associated with poor prognosis in acute myeloid leukemia

Acute myeloid leukemia is the most prevalent type of leukemia in adults and is prone to relapse and chemoresistance, with a low long-term survival rate. Therefore, the identification of quality biomarkers constitutes an urgent unmet need. High expression of beta-1,4-galactosyltransferase 1 (B4GALT1) has been observed in several cancer types; however, its function in acute myeloid leukemia has rarely been studied. Therefore, our study obtained gene expression data from The Cancer Genome Atlas (TCGA) database to analyze the relationship between B4GALT1 and LAML. We compared the expression of B4GALT1 in LAML and healthy samples using the Wilcoxon rank-sum test. Furthermore, the association between B4GALT1 and survival rates was investigated using Kaplan-Meier analysis and Cox regression. The nomogram obtained by Cox analysis predicts the effect of B4GALT1 on the prognosis. To assess B4GALT1-related genes’ enrichment pathway and function and the correlation between B4GALT1 and immune features, GO/KEGG, protein-protein interaction network, and single sample gene set enrichment analysis were used. In addition, B4GALT1-specific siRNAs were used to verify the effect of B4GALT1 on apoptosis. The results showed that B4GALT1 is overexpressed in LAML and has some reference value in the diagnostic and prognostic assessment of LAML. Moreover, functional enrichment showed that B4GALT1 and its 63 associated genes were closely associated with the negative regulation of the apoptotic signaling pathway. Silencing B4GALT1 significantly promoted apoptosis. In addition, B4GALT1 expression was positively correlated with the infiltration levels of macrophages, regulatory T-cell (Tregs), and Th17 cells; in contrast, B4GALT1 expression was negatively correlated with the infiltration levels of T helper cells, Mast cells, and NK cells. In conclusion, our study shows that B4GALT1 may play a vital role in the occurrence of LAML.
Tractography-based navigated TMS language mapping protocol

Introduction This study explores the feasibility of implementing a tractography-based navigated transcranial magnetic stimulation (nTMS) language mapping protocol targeting cortical terminations of the arcuate fasciculus (AF). We compared the results and distribution of errors from the new protocol to an established perisylvian nTMS protocol that stimulated without any specific targeting over the entire perisylvian cortex. Methods Sixty right-handed patients with language-eloquent brain tumors were examined in this study with one half of the cohort receiving the tractographybased protocol and the other half receiving the perisylvian protocol. Probabilistic tractography using MRtrix3 was performed for patients in the tractography-based group to identify the AF’s cortical endpoints. nTMS mappings were performed and resulting language errors were classified into five psycholinguistic groups. Results Tractography and nTMS were successfully performed in all patients. The tractogram-based group showed a significantly higher median overall ER than the perisylvian group (3.8% vs. 2.9% p <.05). The median ER without hesitation errors in the tractogram-based group was also significantly higher than the perisylvian group (2.0% vs. 1.4%, p <.05). The ERs by error type showed no significant differences between protocols except in the no response ER, with a higher median ER in the tractogram-based group (0.4% vs. 0%, p <.05). Analysis of ERs based on the Corina cortical parcellation system showed especially high nTMS ERs over the posterior middle temporal gyrus (pMTG) in the perisylvian protocol and high ERs over the middle and ventral postcentral gyrus (vPoG), the opercular inferior frontal gyrus (opIFG) and the ventral precentral gyrus (vPrG) in the tractography-based protocol. Discussion By considering the white matter anatomy and performing nTMS on the cortical endpoints of the AF, the efficacy of nTMS in disrupting patients’ object naming abilities was increased. The newly introduced method showed proof of concept and resulted in AF-specific ERs and noninvasive cortical language maps, which could be applied to additional fiber bundles related to the language network in future nTMS studies.
On the tidal interaction between protoplanets and the primordial solar nebula. II: Self-consistent nonlinear interaction

On propose une methode pour analyser la reponse non lineaire et les processus physiques associes a l'interaction de maree entre un systeme binaire et un disque fin a l'etat stationnaire. La propagation de l'onde de densite peut etre etudiee pour un large domaine de vitesses du son et de viscosite
Soil heterogeneity in the horizontal distribution of microplastics influences productivity and species composition of plant communities

Contamination of soils by microplastics can have profound ecological impacts on terrestrial ecosystems and has received increasing attention. However, few studies have considered the impacts of soil microplastics on plant communities and none has tested the impacts of spatial heterogeneity in the horizontal distribution of microplastics in the soil on plant communities. We grew experimental plant communities in soils with either a homogeneous or a heterogeneous distribution of each of six common microplastics, i.e., polystyrene foam (EPS), polyethylene fiber (PET), polyethylene bead (HDPE), polypropylene fiber (PP), polylactic bead (PLA) and polyamide bead (PA6). The heterogeneous treatment consisted of two soil patches without microplastics and two with a higher (0.2%) concentration of microplastics, and the homogeneous treatment consisted of four patches all with a lower (0.1%) concentration of microplastics. Thus, the total amounts of microplastics in the soils were exactly the same in the two treatments. Total and root biomass of the plant communities were significantly higher in the homogeneous than in the heterogeneous treatment when the microplastic was PET and PP, smaller when it was PLA, but not different when it was EPS, HDPE or PA6. In the heterogeneous treatment, total and root biomass were significantly smaller in the patches with than without microplastics when the microplastic was EPS, but greater when the microplastic was PET or PP. Additionally, in the heterogeneous treatment, root biomass was significantly smaller in the patches with than without microplastics when the microplastic was HDPE, and shoot biomass was also significantly smaller when the microplastic was EPS or PET. The heterogeneous distribution of EPS in the soil significantly decreased community evenness, but the heterogeneous distribution of PET increased it. We conclude that soil heterogeneity in the horizontal distribution of microplastics can influence productivity and species composition of plant communities, but such an effect varies depending on microplastic chemical composition (types) and morphology (shapes).
Coxsackievirus B3 infection induces glycolysis to facilitate viral replication

Coxsackievirus B3 (CVB3) is a leading cause of viral myocarditis, but no effective treatment strategy against CVB3 is available. Viruses lack an inherent metabolic system and thus depend on host cellular metabolism for their benefit. In this study, we observed that CVB3 enhanced glycolysis in H9c2 rat cardiomyocytes and HL-1 mouse cardiomyocytes. Therefore, three key glycolytic enzymes, namely, hexokinase 2 (HK2), muscle phosphofructokinase (PFKM), and pyruvate kinase M2 (PKM2), were measured in CVB3-infected H9c2 and HL-1 cells. Expression levels of HK2 and PFKM, but not PKM2, were increased in CVB3-infected H9c2 cells. All three key glycolytic enzymes showed elevated expression in CVB3-infected HL-1 cells. To further investigate this, we used 2 deoxyglucose, sodium citrate, and shikonin as glycolysis inhibitors for HK2, PFKM, and PKM2, respectively. Glycolysis inhibitors significantly reduced CVB3 replication, while the glycolysis enhancer dramatically promoted it. In addition, glycolysis inhibitors decreased autophagy and accelerated autophagosome degradation. The autophagy inducer eliminated partial inhibition effects of glycolysis inhibitors on CVB3 replication. These results demonstrate that CVB3 infection enhances glycolysis and thus benefits viral replication.
Impurity effects on drift wave stability and impurity transport

A numerical linear stability analysis of electrostatic ion temperature gradient (ITG) and dissipative trapped electron (DTE) modes in a three-component plasma (electrons, primary ions and impurity ions) is performed using a fully kinetic, sheared slab model. The quasi-linear particle and energy fluxes for each species are also computed. For the ITG mode, it is found that increasing plasma dilution (increasing Zeff) as well as increasing peakedness of the Zeff profile are strongly stabilizing. The quasi-linear calculations of the total anomalous energy flow driven by ITG mode turbulence shows that for Zeff profiles that are nearly flat and of moderately low value (Zeff 2), an energy 'pinch' is possible. A possible connection of this result with recent DIII-D off-axis heating experiments is discussed. A concomitant feature of this inward energy flow is an inward flow of primary ion particles, and an outward flow of impurity ion particles that greatly exceeds the neoclassical level. The impurity effects on the DTE mode are opposite, i.e. increasing dilution and Zeff profile peakedness are strongly destabilizing. As a result, quasi-linear theory predicts a large increase in the anomalous electron energy flux and much smaller effects on the anomalous fluxes of the ion species
Native and engineered extracellular vesicles for wound healing

Extracellular vesicles (EVs) that act as messengers mediate communication between parent and recipient cells through their contents, including nucleic acids, proteins, and lipids. These endogenous vesicles have emerged as a novel cell-free strategy for the treatment of diseases. EVs can be released by various types of cells with unique biological properties. Recent studies have shown that native EVs are used as therapeutic agents to promote tissue repair by delivering various growth factors and trophic factors including VEGF, EGF, TFN-α, IL-1β, and TGF-β to participate in all physiological processes of wound healing. Furthermore, to improve their specificity, safety, and efficiency for wound healing, the content and surface of EVs can be designed, modified, and engineered. The engineering strategies of EVs are divided into parent cell modification and indirect modification of EVs. The therapeutic potential of current EVs and engineered EVs for wound healing still requires the exploration of their large-scale clinical applications through innovative approaches. Herein, we provide an overview of the current biological knowledge about wound healing and EVs, as well as the application of native EVs in promoting wound healing. We also outline recent advances in engineering EV methodologies to achieve ideal therapeutic potential. Finally, the therapeutic applications of engineered EVs in wound healing are reviewed, and the challenges and prospects for the translation of engineered EVs to clinical applications are discussed.