Miracle-dz/UniFAR-FTUs huggingface dataset:
MOESI-prime: preventing coherence-induced hammering in commodity workloads

Prior work shows that Rowhammer attacks---which flip bits in DRAM via frequent activations of the same row(s)---are viable. Adversaries typically mount these attacks via instruction sequences that are carefully-crafted to bypass CPU caches. However, we discover a novel form of hammering that we refer to as coherence-induced hammering, caused by Intel's implementations of cache coherent non-uniform memory access (ccNUMA) protocols. We show that this hammering occurs in commodity benchmarks on a major cloud provider's production hardware, the first hammering found to be generated by non-malicious code. Given DRAM's rising susceptibility to bit flips, it is paramount to prevent coherence-induced hammering to ensure reliability and security in the cloud. Accordingly, we introduce MOESI-prime, a ccNUMA coherence protocol that mitigates coherence-induced hammering while retaining Intel's state-of-the-art scalability. MOESI-prime shows that most DRAM reads and writes triggering such hammering are unnecessary. Thus, by encoding additional information in the coherence protocol, MOESI-prime can omit these reads and writes, preventing coherence-induced hammering in non-malicious and malicious workloads. Furthermore, by omitting unnecessary reads and writes, MOESI-prime has negligible effect on average performance (within ±0.61% of MESI and MOESI) and average DRAM power (0.03%-0.22% improvement) across evaluated ccNUMA configurations.
Efficiency of Peruvian regions in the management of hospital resources against COVID-19 in 2020: A two stage DEA model

In the aftermath of the COVID-19 health crisis, hospitals around the world needed to stock up on resources to satisfy the high demand from patients. Peru was one of the countries most affected by the pandemic due to its fragile health system that led it to be the country with the highest mortality rate in the world with 554 deaths per million inhabitants. For this reason, it was imperative to implement measures to mitigate the state of emergency, such as the allocation of health resources to hospitals in all regions of the country. This research aimed to measure the efficiency of the Peruvian regions in the management of hospital resources against COVID-19 at the end of the year 2020. The two stage DEA model, the Data Envelopment Analysis in the first stage was used to estimate the efficiency and the Logit regression model in the second stage to find the incidence of internal and external factors. To this end, the variables number of doctors, number of nurses, oxygen, number of medications, number of COVID tests, number of positive cases, ICU beds available as inputs, and as outputs the mortality rate and recovery rate were selected; then, 8 models were formulated that grouped these variables sequentially to estimate efficiency. Results indicated that 53.33% of the regions were inefficient in all the proposed models, only Amazonas and Huancavelica regions were efficient in 2020, when comparing the average efficiency of each model, it was possible to distinguish that the internal variables of the number of nurses and oxygen causes a significant change in efficiency. Logit regression concluded that the number of nurses and the total population are significant influencing variables, while the external variable GDP per capita had a negative effect on the efficiency scores. Important findings show a notable deficiency in the use of human resources and poor management of investment in health resources to face the COVID-19 pandemic in Peru.
Gearbox: a case for supporting accumulation dispatching and hybrid partitioning in PIM-based accelerators

Processing-in-memory (PIM) minimizes data movement overheads by placing processing units near each memory segment. Recent PIMs employ processing units with a SIMD architecture. However, kernels with random accesses, such as sparse-matrix-dense-vector (SpMV) and sparse-matrix-sparse-vector (SpMSpV), cannot effectively exploit the parallelism of SIMD units because SIMD's ALUs remain idle until all the operands are collected from local memory segments (memory segment attached to the processing unit) or remote memory segments (other segments of the memory). For SpMV and SpMSpV, properly partitioning the matrix and the vector among the memory segments is also very important. Partitioning determines (i) how much processing load will be assigned to each processing unit and (ii) how much communication is required among the processing units. In this paper, first, we propose a highly parallel architecture that can exploit the available parallelism even in the presence of random accesses. Second, we observed that, in SpMV and SpMSpV, most of the remote accesses become remote accumulations with the right choice of algorithm and partitioning. The remote accumulations could be offloaded to be performed by processing units next to the destination memory segments, eliminating idle time due to remote accesses. Accordingly, we introduce a dispatching mechanism for remote accumulation offloading. Third, we propose Hybrid partitioning and associated hardware support. Our partitioning technique enables (i) replacing remote read accesses with broadcasting (for only a small portion of data that will be read by all processing units), (ii) reducing the number of remote accumulations, and (iii) balancing the load. Our proposed method, Gearbox, with just one memory stack, delivers on average (up to) 15.73X (52X) speedup over a server-class GPU, NVIDIA P100, with three stacks of HBM2 memory.
Interest Flooding Attacks in Named Data Networking: Survey of Existing Solutions, Open Issues, Requirements, and Future Directions

Named Data Networking (NDN) is a prominent realization of the vision of Information-Centric Networking. The NDN architecture adopts name-based routing and location-independent data retrieval. Among other important features, NDN integrates security mechanisms and focuses on protecting the content rather than the communications channels. Along with a new architecture come new threats, and NDN is no exception. NDN is a potential target for new network attacks such as Interest Flooding Attacks (IFAs). Attackers take advantage of IFA to launch (D)DoS attacks in NDN. Many IFA detection and mitigation solutions have been proposed in the literature. However, there is no comprehensive review study of these solutions that has been proposed so far. Therefore, in this article, we propose a survey of the various IFAs with a detailed comparative study of all the relevant proposed solutions as counter-measures against IFAs. We also review the requirements for a complete and efficient IFA solution and pinpoint the various issues encountered by IFA detection and mitigation mechanisms through a series of attack scenarios. Finally, in this survey, we offer an analysis of the open issues and future research directions regarding IFAs.
Automatic Interpretable Personalized Learning

Personalized learning stems from the idea that students benefit from instructional material tailored to their needs. Many online learning platforms purport to implement some form of personalized learning, often through on-demand tutoring or self-paced instruction, but to our knowledge none have a way to automatically explore for specific opportunities to personalize students' education nor a transparent way to identify the effects of personalization on specific groups of students. In this work we present the Automatic Personalized Learning Service (APLS). The APLS uses multi-armed bandit algorithms to recommend the most effective support to each student that requests assistance when completing their online work, and is currently used by ASSISTments, an online learning platform. The first empirical study of the APLS found that Beta-Bernoulli Thompson Sampling, a popular and effective multi-armed bandit algorithm, was only slightly more capable of selecting helpful support than randomly selecting from the relevant support options. Therefore, we also present Decision Tree Thompson Sampling (DTTS), a novel contextual multi-armed bandit algorithm that integrates the transparency and interpretability of decision trees into Thomson sampling. In simulation, DTTS overcame the challenges of recommending support within an online learning platform and was able to increase students' learning by as much as 10% more than the current algorithm used by the APLS. We demonstrate that DTTS is able to identify qualitative interactions that not only help determine the most effective support for students, but that also generalize well to new students, problems, and support content. The APLS using DTTS is now being deployed at scale within ASSISTments and is a promising tool for all educational learning platforms.
The variable viscoelasticity oscillator

The complex dynamics of a variable viscoelasticity oscillator is studied using the novel concept of Variable‐Order (VO) Calculus. The damping force in the oscillator varies continuously between the elastic and viscous regimes depending on the position of the mass. The oscillator considered here is composed of a linear spring of stiffness k that inputs a restitutive force Fk = ‐k x, a VO damper of order q(x(t)) that generates a damping force Fq = ‐cq 𝒟q(x(t)) x, and a mass m. A modified Runge‐Kutta method is used in conjunction with a trapezoidal numerical integration technique to yield a second‐order accurate method for the solution of the resulting VO Differential Equation (VODE). The VO oscillator is also modelled using a Constant Order (CO) formulation where a number of CO fractional order differentials are weighted to simulate the VO behavior. The CO formulation asymptotically approaches the VO results when a relatively large number of weights is used. For the viscoelastic range of 0 ≤ q ≤ 1, the dynamics of the oscillator is well approximated by the CO formulation when 5 or more fractional terms are included (e.g., 0, 1/4, 1/2, 3/4, and 1).
Pemafibrate for primary biliary cholangitis with dyslipidemia: A proposal of a new treatment from Japan

Liver is a central organ of bile acid (BA) metabolism. BA is synthe-sized from cholesterol via cytochrome P450 7A1 and is excreted into bile duct after the conjugation with taurine, glycine, glucuronic acid, and sulfate. In the intestine, BA emulsifies dietary lipids and goes back to the liver as the component of micelles. Additionally, BA modulates the composition of microbiota and gut bacteria syn-thesize various types of BAs in response to dietary composition and intestinal environment. BA is regarded as a key metabolite informing the condition of intestine, as well as nutritional and metabolic status. Nuclear receptors (NRs) regulate nutrient metabolism and main-tain energy homeostasis through controlling the transcriptional levels of several genes. 1 ‐ 3 Ligands of NR include both endogenous and exogenous lipophilic molecules/metabolites, such as fatty acids (FAs), vitamins, drugs, and toxins. Although BAs are essential for digestion/ absorption of dietary fat, some BAs are potentially cytotoxic due to its hydrophobicproperty.Therefore,itisreasonablethatsomeNRssense hepatic BA levels and regulate BA metabolism ‐ related genes to mini-mize BA toxicity. For example, farnesoid X receptor (FXR) is activated by some BAs, such as chenodeoxycholic acid, and suppresses CYP7A1 and enhances BA excretion from the liver. Pregnane X receptor (PXR), a typical xenobiotic NR, is activated by microbially derived second-ary hydrophobic (median follow ‐ up period: 9 years) significantly improved the serum alkaline phosphatase levels and the Mayo risk score compared with UDCA monotherapy, but significantly increased the serum creatinine levels and did not improve the survival rate. 8 It is expected that long ‐ term treatment of PEM attenuates the severity of PBC without worsening renal function. Third, it should be confirmed whether PEM can improve not only biliary enzymes, but also liver histology and PBC ‐ related symptoms, such as pruritis. Lastly, the effectiveness and safety of other serious cholestatic liver diseases should be evaluated. Primary sclerosing cholangitis (PSC) is sometimes refractory to UDCA monotherapy and may lead to end ‐ stage liver disease requiring liver transplantation, so the efficacy of PEM add ‐ on to PSC with dyslipidemia is of great interest. In conclusion, PEM, developed in Japan, would be a new prom-ising therapeutic option for PBC with dyslipidemia.
A variable order constitutive relation for viscoelasticity

A constitutive relation for linear viscoelasticity of composite materials is formulated using the novel concept of Variable Order (VO) differintegrals. In the model proposed in this work, the order of the derivative is allowed to be a function of the independent variable (time), rather than a constant of arbitrary order. We generalize previous works that used fractional derivatives for the stress and strain relationship by allowing a continuous spectrum of non‐integer dynamics to describe the physical problem. Starting with the assumption that the order of the derivative is a measure of the rate of change of disorder within the material, we develop a statistical mechanical model that is in agreement with experimental results for strain rates varying more than eight orders of magnitude in value. We use experimental data for an epoxy resin and a carbon/epoxy composite undergoing constant compression rates in order to derive a VO constitutive equation that accurately models the linear viscoelastic deformation in time. The resulting dimensionless constitutive equation agrees well with all the normalized data while using a much smaller number of empirical coefficients when compared to available models in the literature.
The “writing on the cosmic wall”: Is there a straightforward explanation of the cosmic microwave background?

The Cosmic Microwave Background (CMB) is taken today as reflecting the thermodynamical state of the universe at these early cosmic times. Based on this assumption and standard cosmological principles meanwhile many fundamental cosmological facts have been deduced from the CMB state which, however, to some surprise reveal that the universe should be dominated by dark energy and dark matter, while for its energy content the usual baryonic matter is nearly negligible. Thus the question which we want to raise in this article is, whether this standard interpretation of the CMB phenomenon is solid and unequivocal enough to support the standard cosmological claims. We shall show, however, that in many details the standard explanation is not straightforward, but allows for important alternatives which seriously should be looked at. Especially arguments for a vanishing cosmic curvature (k = 0) are shown to be weak, and, contrary to the usual claim, the light distance to the recombination horizon is in fact strongly model‐biassed. We also show that the CMB dipole which is generally understood as a consequence of a peculiar motion by about 680 km/s with respect to rest system of the CMB can as well, and perhaps even better, be understood as indication of differerent cosmological expansion dynamics seen in an anisotropically expanding universe in different directions of the sky. We also discuss that the power amplitude (i.e. effective Planck temperature) in the dipolar CMB structure depends on wavelength even inverting the dipole maximum orientation in the Wien's branch. In addition unexpected properties of the lowest CMB multipoles could mean that we are at least partly seeing an unquantifyable foreground in the background. Only after its removal the CMB interpretation could at all then, but then on a completely new basis, become a subject of cosmological terms. At the end of this article we shall briefly discuss an alternative explanation of the CMB radiation which helps to better understand the mysterious cosmic photon‐to‐baryon ratio of about 109.
Food Flows and the Roles of Cities in West African Food Distribution Networks

In West Africa, rampant urbanization is changing food systems, including the magnitude and composition of food flows and the length of supply chains. An increasing body of literature discusses pathways to sustainable transformation of urban food systems taking into account links between urban and rural spaces. Research and policy have focused on the role of cities as consumption centers receiving food from local, regional, and global hinterlands. This study aims at widening the perspective on the role of cities in food distribution, by bringing into focus a city's function as a consumption, aggregation, and disaggregation center. The analysis is based on a comprehensive set of primary data on food flows collected in four West African cities across different seasons. The analysis shows that the investigated cities are integrated into multi-scale urban and market networks. Their position within these networks interacts with their reliance on other territories for food supply and with their functions, such as the aggregation of goods. The capital cities of Ouagadougou (Burkina Faso) and Bamako (Mali) relied more on lower-rank urban settlements further away, while Tamale, a secondary city in Ghana, acted as an assembly market for local rural producers and in turn supplied larger urban centers. Bamenda, a secondary city in Cameroon, acted as a consumption center sourcing mainly from its hinterland. Beyond that, city functions were context-specific and varied according to type of product and season. Extending the perspective on the role of cities has implications for policy, including bringing into focus and strengthening midstream segments, such as market and transport links.
Anxiety, Worry, Life Satisfaction and Coping During the Acute VS Prolonged Pandemic Stress: Evidence From a Repeated Cross-Sectional Study

Objectives: The COVID-19 pandemic remains a continuous stressor worldwide. Our study aimed at comparing the data of waves from two lockdowns in Georgia, one in the acute stress phase (May 2020) and the other in the prolonged stress phase (December 2020). Methods: In total, 750 and 716 individuals participated in the study with a repeated cross-sectional design. Sample equivalence was reached via controlling demographic variables. Anxiety, COVID-19 worry, and life satisfaction were measured along with coping behaviors and four coping styles—information-accessing/processing and action-planning (two problem-focused coping styles), and passive-submissive and avoidant (two emotion-focused coping styles). Results: As pandemic prolonged, mental health indicators worsened, the action-planning style and behavioral coping decreased, while the information-accessing/processing style increased. The link between the COVID-19 worry and the action-planning coping style was strong in the acute stage and dissapeared in the prolonged stage. The individual context, namely, a history of coronavirus in the household, accounted for lower protective behaviors and higher information seeking in the prolonged phase. Conclusion: The findings highlighted the importance of timing and general and individual contexts in coping with the pandemic.
Identification of Core Genes and Screening of Potential Targets in Intervertebral Disc Degeneration Using Integrated Bioinformatics Analysis

Background: Intervertebral disc degeneration (IDD), characterized by diverse pathological changes, causes low back pain (LBP). However, prophylactic and delaying treatments for IDD are limited. The aim of our study was to investigate the gene network and biomarkers of IDD and suggest potential therapeutic targets. Methods: Differentially expressed genes (DEGs) associated with IDD were identified by analyzing the mRNA, miRNA, and lncRNA expression profiles of IDD cases from the Gene Expression Omnibus (GEO). The protein–protein interaction (PPI) network, Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis as well as miRNA–lncRNA–mRNA networks were conducted. Moreover, we obtained 71 hub genes and performed a comprehensive analysis including GO, KEGG, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), Disease Ontology (DO), methylation analysis, receiver operating characteristic (ROC) curve analysis, immune infiltration analysis, and potential drug identification. We finally used qRT-PCR to verify 13 significant DEGs in normal and degenerative nucleus pulposus cells (NPCs). Results: We identified 305 DEGs closely related to IDD. The GO and KEGG analyses indicated that changes in IDD are significantly associated with enrichment of the inflammatory and immune response. GSEA analysis suggested that cell activation involved in the inflammatory immune response amide biosynthetic process was the key for the development of IDD. The GSVA suggested that DNA repair, oxidative phosphorylation, peroxisome, IL-6-JAK-STAT3 signaling, and apoptosis were crucial in the development of IDD. Among the 71 hub genes, the methylation levels of 11 genes were increased in IDD. A total of twenty genes showed a high functional similarity and diagnostic value in IDD. The result of the immune cell infiltration analysis indicated that seven genes were closely related to active natural killer cells. The most relevant targeted hub genes for potential drug or molecular compounds were MET and PIK3CD. Also, qRT-PCR results showed that ARHGAP27, C15orf39, DEPDC1, DHRSX, MGAM, SLC11A1, SMC4, and LINC00887 were significantly downregulated in degenerative NPCs; H19, LINC00685, mir-185-5p, and mir-4306 were upregulated in degenerative NPCs; and the expression level of mir-663a did not change significantly in normal and degenerative NPCs. Conclusion: Our findings may provide new insights into the functional characteristics and mechanism of IDD and aid the development of IDD therapeutics.
A Bibliometric Analysis of Triptolide and the Recent Advances in Treating Non–Small Cell Lung Cancer

In recent decades, natural products derived from plants and their derivatives have attracted great interest in the field of disease treatment. Triptolide is a tricyclic diterpene extracted from Tripterygium wilfordii, a traditional Chinese medicine, which has shown excellent therapeutic potential in the fields of immune inflammation and cancer treatment. In this study, 1,106 Web-of-Science-indexed manuscripts and 1,160 Chinese-National-Knowledge-Infrastructure-indexed manuscripts regarding triptolide published between 2011 and 2021 were analyzed, mapping the co-occurrence networks of keywords and clusters using CiteSpace software. The research frontier and development trend were determined by keyword frequency and cluster analysis, which can be used to predict the future research development of triptolide. Non–small cell lung cancer (NSCLC) is most common in lung cancer patients, accounting for about 80% of all lung cancer patients. New evidence suggests that triptolide effectively inhibits the development and metastasis of NSCLC by the induction of apoptosis, reversion of EMT, and regulation of gene expression. Specifically, it acts on NF-κB, MAPKs, P53, Wnt/β-catenin, and microRNAs (miRNAs), signaling pathways and molecular mechanisms. Consequently, this article reviews the research progress of the anti-NSCLC effect of triptolide. In addition, attenuated studies on triptolide and the potential of tumor immunotherapy are also discussed.