Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent Advances in DRAM and Flash Memory Architectures

This article features extended summaries and retrospectives of some of the recent research done by our group, SAFARI, on (1) understanding, characterizing, and modeling various critical properties of modern DRAM and NAND flash memory, the dominant memory and storage technologies, respectively; and (2) several new mechanisms we have proposed based on our observations from these analyses, characterization, and modeling, to tackle various key challenges in memory and storage scaling. In order to understand the sources of various bottlenecks of the dominant memory and storage technologies, these works perform rigorous studies of device-level and application-level behavior, using a combination of detailed simulation and experimental characterization of real memory and storage devices.
NetLSD: Hearing the Shape of a Graph

Comparison among graphs is ubiquitous in graph analytics. However, it is a hard task in terms of the expressiveness of the employed similarity measure and the efficiency of its computation. Ideally, graph comparison should be invariant to the order of nodes and the sizes of compared graphs, adaptive to the scale of graph patterns, and scalable. Unfortunately, these properties have not been addressed together. Graph comparisons still rely on direct approaches, graph kernels, or representation-based methods, which are all inefficient and impractical for large graph collections. In this paper, we propose the Network Laplacian Spectral Descriptor (NetLSD): the first, to our knowledge, permutation- and size-invariant, scale-adaptive, and efficiently computable graph representation method that allows for straightforward comparisons of large graphs. NetLSD extracts a compact signature that inherits the formal properties of the Laplacian spectrum, specifically its heat or wave kernel; thus, it \em hears the shape of a graph. Our evaluation on a variety of real-world graphs demonstrates that it outperforms previous works in both expressiveness and efficiency.
A Sequential Embedding Approach for Item Recommendation with Heterogeneous Attributes

Attributes, such as metadata and profile, carry useful information which in principle can help improve accuracy in recommender systems. However, existing approaches have difficulty in fully leveraging attribute information due to practical challenges such as heterogeneity and sparseness. These approaches also fail to combine recurrent neural networks which have recently shown effectiveness in item recommendations in applications such as video and music browsing. To overcome the challenges and to harvest the advantages of sequence models, we present a novel approach, Heterogeneous Attribute Recurrent Neural Networks (HA-RNN), which incorporates heterogeneous attributes and captures sequential dependencies in \textit{both} items and attributes. HA-RNN extends recurrent neural networks with 1) a hierarchical attribute combination input layer and 2) an output attribute embedding layer. We conduct extensive experiments on two large-scale datasets. The new approach show significant improvements over the state-of-the-art models. Our ablation experiments demonstrate the effectiveness of the two components to address heterogeneous attribute challenges including variable lengths and attribute sparseness. We further investigate why sequence modeling works well by conducting exploratory studies and show sequence models are more effective when data scale increases.
Differentiable Particle Filters: End-to-End Learning with Algorithmic Priors

We present differentiable particle filters (DPFs): a differentiable implementation of the particle filter algorithm with learnable motion and measurement models. Since DPFs are end-to-end differentiable, we can efficiently train their models by optimizing end-to-end state estimation performance, rather than proxy objectives such as model accuracy. DPFs encode the structure of recursive state estimation with prediction and measurement update that operate on a probability distribution over states. This structure represents an algorithmic prior that improves learning performance in state estimation problems while enabling explainability of the learned model. Our experiments on simulated and real data show substantial benefits from end-to- end learning with algorithmic priors, e.g. reducing error rates by ~80%. Our experiments also show that, unlike long short-term memory networks, DPFs learn localization in a policy-agnostic way and thus greatly improve generalization. Source code is available at this https URL .
A UTILIZAÇÃO DO MÉTODO DA UNIDADE DE ESFORÇO DE PRODUÇÃO NA QUANTIFICAÇÃO DAS PERDAS INTERNAS DA EMPRESA

Entre as informacoes necessarias para o efetivo auxilio ao controle e avaliacao da empresa moderna, sem duvida a mensuracao das perdas e das atividades que nao agregam valor aos produtos e das mais importantes, pois, com tal informacao, e possivel visualizar-se o montante despendido no sistema produtivo que nao colabora para a fabricacao dos produtos, tendo-se condicoes de priorizar e dirigir esforcos de melhoria aos locais onde existe maior potencial de retorno. O presente trabalho propoe uma metodologia para a utilizacao do metodo da UEP na mensuracao das perdas internas do processo produtivo da empresa e na criacao de indicadores para controle das mesmas. A metodologia proposta nao avalia custos de materiais, os quais sao melhor analisados pelo metodo do custo padrao.
Illumina MiSeq Sequencing for Preliminary Analysis of Microbiome Causing Primary Endodontic Infections in Egypt

The use of high throughput next generation technologies has allowed more comprehensive analysis than traditional Sanger sequencing. The specific aim of this study was to investigate the microbial diversity of primary endodontic infections using Illumina MiSeq sequencing platform in Egyptian patients. Samples were collected from 19 patients in Suez Canal University Hospital (Endodontic Department) using sterile # 15K file and paper points. DNA was extracted using Mo Bio power soil DNA isolation extraction kit followed by PCR amplification and agarose gel electrophoresis. The microbiome was characterized on the basis of the V3 and V4 hypervariable region of the 16S rRNA gene by using paired-end sequencing on Illumina MiSeq device. MOTHUR software was used in sequence filtration and analysis of sequenced data. A total of 1858 operational taxonomic units at 97% similarity were assigned to 26 phyla, 245 families, and 705 genera. Four main phyla Firmicutes, Bacteroidetes, Proteobacteria, and Synergistetes were predominant in all samples. At genus level, Prevotella, Bacillus, Porphyromonas, Streptococcus, and Bacteroides were the most abundant. Illumina MiSeq platform sequencing can be used to investigate oral microbiome composition of endodontic infections. Elucidating the ecology of endodontic infections is a necessary step in developing effective intracanal antimicrobials.
Epstein-Barr virus-encoded microRNAs as regulators in host immune responses

Epstein-Barr virus (EBV) is an oncogenic virus that infects over 90% of the world's adult population. EBV can establish life-long latent infection in host due to the balance between EBV and host immune system. EBV latency is associated with various malignancies such as nasopharyngeal carcinoma, gastric carcinoma and Burkitt's lymphoma. EBV is the first human virus that has the capability to encode microRNAs (miRNAs). Remarkably, EBV-encoded miRNAs are abundantly expressed in latently-infected cells and serve important function in viral infection and pathogenesis. Increasing evidence indicates that EBV miRNAs target the host mRNAs involved in cell proliferation, apoptosis and transformation. EBV miRNAs also inhibit the expression of viral antigens, thereby enabling infected cells to escape immune recognition. Intriguingly, EBV miRNAs directly suppress host antiviral immunity by interfering with antigen presentation and immune cell activation. This review will update the current knowledge about EBV miRNAs implicated in host immune responses. An in-depth understanding of the functions of EBV miRNAs in host antiviral immunity will shed light on the EBV-host interactions and provide potential therapeutic targets for the treatment of EBV-associated malignancies.
Multi-class classification of pulmonary endomicroscopic images

Optical endomicroscopy (OEM) is an emerging medical imaging tool capable of providing in-vivo, in-situ optical biopsies. Clinical pulmonary OEM procedures generate data containing a multitude of frames, making their manual analysis a highly subjective and laborious task. It is therefore essential to automatically classify the images into clinically relevant classes to aid reaching a fast and reliable diagnosis. This paper proposes a methodology to automatically classify OEM images of the distal lung. Due to their diagnostic relevance, three classification tasks are targeted: (i) differentiating between alveolar images containing predominantly elastin from those flooded with cells, (ii) separating normal from abnormal elastin frames, and (iii) multi-class classification amongst normal, abnormal, and cell frames. Local Binary Patterns along with a Support Vector Machine classifier, and One-Versus-All Error Correcting Output Codes strategy for the multi-class classification case, are employed obtaining accuracy of 92.2%, 95.2%, 90.1% for the tasks (i), (ii), (iii), respectively.
iHDViewer: A Visualization Tool for Tracking HD

Visualization techniques on hierarchical information have been proved their capability in presenting structured disk storage data. However, most existing techniques represented with simple visual methods such as pie chart or histogram, lacking the ability of grasping the usage of the computer. This paper presents a new interactive visualization technique named iHard Disk Viewer (iHDViewer), which aims to display file details and their movement histories, as well as predict the user's activities through visualization results. This tool mainly utilizes four different view panels to display the distribution of files and file folders for a computer system. Specifically, A tree view explains the general distribution of the whole disk storage; A river trend view tracks the files moving history, which is implemented by cubic spline interpolator with restricted boundary conditions to ensure the trend stability and information accuracy; We also use the concept of coordinate extension to visualize the file moving events which supports more intuitive results; A filelist view panel shows the details of the selected files; while a circle view panel interactively displays the status of files and file folders. In addition, considering the importance of human visual perception system in the data analyzing processes, we utilize three color design principles to work through all visual methods. Lastly, this paper demonstrates the effectiveness and efficiency of our new idea to visually analyze computer FileSystems.
TxPI-u: A resource for Personality Identification of undergraduates

Resources such as labeled corpora are necessary to train automatic models within the natural language processing (NLP) field. Historically, a large number of resources regarding a broad number of problems are available mostly in English. One of such problems is known as Personality Identification where based on a psychological model (e.g. The Big Five Model), the goal is to find the traits of a subject's personality given, for instance, a text written by the same subject. In this paper we introduce a new corpus in Spanish called Texts for Personality Identification (TxPI). This corpus will help to develop models to automatically assign a personality trait to an author of a text document. Our corpus, TxPI-u, contains information of 416 Mexican undergraduate students with some demographics information such as, age, gender, and the academic program they are enrolled. Finally, as an additional contribution, we present a set of baselines to provide a comparison scheme for further research.
Coextrusion-Based 3D Plotting of Ceramic Pastes for Porous Calcium Phosphate Scaffolds Comprised of Hollow Filaments

This paper demonstrates the utility of coextrusion-based 3D plotting of ceramic pastes (CoEx-3DP) as a new type of additive manufacturing (AM) technique, which can produce porous calcium phosphate (CaP) ceramic scaffolds comprised of hollow CaP filaments. In this technique, green filaments with a controlled core/shell structure can be produced by coextruding an initial feedrod, comprised of the carbon black (CB) core and CaP shell, through a fine nozzle in an acetone bath and then deposited in a controlled manner according to predetermined paths. In addition, channels in CaP filaments can be created through the removal of the CB cores during heat-treatment. Produced CaP scaffolds had two different types of pores with well-defined geometries: three-dimensionally interconnected pores (~360 × 230 μm2 in sizes) and channels (>100 μm in diameter) in hollow CaP filaments. The porous scaffolds showed high compressive strengths of ~12.3 ± 2.2 MPa at a high porosity of ~73 vol % when compressed parallel to the direction of the hollow CaP filaments. In addition, the mechanical properties of porous CaP scaffolds could be tailored by adjusting their porosity, for example, compressive strengths of 4.8 ± 1.1 MPa at a porosity of ~82 vol %. The porous CaP scaffold showed good biocompatibility, which was assessed by in vitro cell tests, where several the cells adhered to and spread actively with the outer and inner surfaces of the hollow CaP filaments.
Coral Ultrastructural Response to Elevated pCO2 and Nutrients During Tissue Repair and Regeneration

Corals and coral reefs have recently experienced widespread decline attributed to anthropogenic pressure on reef systems. Studies have demonstrated that nutrient and pCO2 stress effect coral growth and calcification, but study of specific effects on coral tissue is lacking. The objective of this research was to examine wound healing in corals and how it is affected by exposure to elevated nutrients and pCO2. Coral tissue repair and regeneration during wound healing in Montastraea cavernosa and Porites astreoides were assessed histologically and ultrastructurally by examining colony fragments exposed to elevated nitrate, phosphate, and pCO2. In M. cavernosa, tissue repair was facilitated by granular amoebocytes, and the zooxanthellae population size increased under enriched nutrient conditions. In P. astreoides, zooxanthellae chloroplasts were markedly abnormal in phosphate-enriched corals, and the concentration of chromophore cells at the healing tissue front was markedly lower under elevated nutrient conditions. The area of wound healed was higher after 14 days under every experimental condition in M. cavernosa compared to P. astreoides. In both species, phosphate enrichment had the most deleterious effect on repair and regeneration.
The Use of Complementary and Alternative Medicine Is Less Frequent in Patients with Inflammatory Bowel Disease Than in Patients with Other Chronic Gastrointestinal Disorders

Background and Aims Complementary and alternative medicine (CAM) is commonly used among patients with inflammatory bowel diseases (IBD), but evidence about its real-life use is limited. We aimed to assess and compare CAM use in outpatients with IBD and other gastrointestinal diseases. Materials and Methods The use of herbs and botanicals, lifestyle modifications and mind/body therapies, patient satisfaction, and continuous use of conventional medicine were assessed with an anonymous questionnaire at a tertiary IBD unit in Hungary. 396 IBD patients (207 with Crohn's disease, 185 with ulcerative colitis, and 4 with indeterminate colitis) and 164 patients with gastric acid-related diseases, premalignant and malignant colorectal diseases, lactose intolerance, celiac disease, dysbacteriosis, and so on were included. Results IBD patients reported significantly lower usage of herbs than did controls (25% versus 42%, p < 0.001). More than 90% of responding IBD patients continued conventional medication besides herbal remedies (83% in unaltered doses). IBD patients were more likely to implement lifestyle modifications (77% versus 63%, p = 0.0011), but not body/mind therapies (20% versus 15%, p = 0.1516). Younger age was a significant predictor of lifestyle modifications (p = 0.0246). Conclusions CAM use (especially that of herbal remedies) in IBD is less frequent than that in other gastrointestinal diseases. It is more a complementary than an alternative to conventional medicine in IBD. There is no significant difference between CAM use in patients with Crohn's disease and that in patients with ulcerative colitis, although the latter tend to choose herbs; the benefit of which is supported by scientific evidence. This study is registered at the Medical Research Council, Hungary. This trial is registered with 3769/2010/1018EKU.
Finger vein and finger texture based biometrie approach for personal identification

Authentication is considered as primary issue with respect to trust when security protocols are taken into account. Biometrics is rather adopted and used widely as a promising authentication method due to its advantages in resisting to losses incurred by theft of passwords and smart cards. However, biometrics is a challenging area which introduces privacy concern. In this paper, Finger vein recognition is considered for Biometric authentication system. This is one among many kinds of biometrics used and to verify the identity. The proposed framework gets the finger-vein and finger-texture images at a time. Camera is used to obtain the finger vein and finger texture images. The utility of low-determination finger vein and finger texture images is analyzed to learn the coordinating execution. The low determination images are improved by joining the upgrade strategy Contrast Limited Adaptive Histogram Equalization (CLAHE) and middle filter. The division of Region Of Interest (ROI) at various determination levels and the pivot interpretations makes the framework profoundly proficient. This paper presents a recognizable method Gabor Filter for highlight extraction handle which enhances the general exactness of the framework. The entire list of capabilities is enlightening in nature and lessens the Equal Error Rate. Two new score-level combinations i.e., all-encompassing and nonlinear combination have been developed to produce the joined coordinating score's to find out their adequacy in the proposed framework. The proposed approach shows its predominance over earlier distributed endeavor and displayed that the framework is exceedingly precise.
The Golf Shaft’s Influence on Clubhead-Ball Impact Dynamics

A long-held assumption in golf research is that the driver-ball impact is accurately modelled as a collision between two free bodies, i.e., the clubhead is not attached to the shaft. The purpose of this work was to examine the validity of this assumption using multibody simulation and motion capture technology. Ten elite golfers were recruited to participate in a motion capture experiment to validate a Rayleigh beam model of a flexible club. Using the six degree-of-freedom motion of the grip as an input to the model, the simulated shaft deflections showed good agreement with the experiment. An impact model based on volumetric contact was integrated with the flexible club model and was used to compare the launch conditions of free-body and full-club impacts. Analysis of the launch conditions revealed that the shaft creates a stiffening effect that resists clubhead rotation during contact, corresponding to an increase in ball speed and suppression of the gear-effect relative to free-body impacts. The results demonstrate that shaft dynamics cannot be treated as negligible when evaluating driver impact mechanics.
Frequency Division Based Coordinated Control of Three-Port Converter Interfaced Hybrid Energy Storage Systems in Autonomous DC Microgrids

DC microgrids (MGs) feature remarkable advantages of integrating renewable energy sources and loads with DC coupling. In order to improve the operation performance of a dc MG in both steady and transient states, in this paper a hybrid energy storage system (HESS) interfaced by a three-port converter (TPC) is studied. Particularly, a battery and an ultra-capacitor (UC), which form the HESS, are connected at the source side of the TPC, respectively. Aiming at a phase-shifting controlled full-bridge isolated TPC, in addition to conventional droop control loop, a frequency division-based control method is proposed to achieve rational power sharing between the battery and UC. Due to the characteristics of TPC, virtual inductance and virtual capacitance loops are implemented using the input currents at the battery and UC ports. The frequency division between the battery and UC in the HESS is quantitatively analyzed by using the frequency domain small-signal analysis considering the characteristics of power exchange in the phase-shifting controlled TPC. A simulation model built in MATLAB/Simulink and a prototype comprised of a battery, a UC, a programmable dc load, and auxiliary components are implemented to validate the proposed TPC-interfaced HESS under different operation scenarios.
AKR1B10 activates diacylglycerol (DAG) second messenger in breast cancer cells

Aldo‐keto reductase 1B10 (AKR1B10) is upregulated in breast cancer and promotes tumor growth and metastasis. However, little is known of the molecular mechanisms of action. Herein we report that AKR1B10 activates lipid second messengers to stimulate cell proliferation. Our data showed that ectopic expression of AKR1B10 in breast cancer cells MCF‐7 promoted lipogenesis and enhanced levels of lipid second messengers, including phosphatidylinositol bisphosphate (PIP2), diacylglycerol (DAG), and inositol triphosphate (IP3). In contrast, silencing of AKR1B10 in breast cancer cells BT‐20 and colon cancer cells HCT‐8 led to decrease of these lipid messengers. Qualitative analyses by liquid chromatography‐mass spectrum (LC‐MS) revealed that AKR1B10 regulated the cellular levels of total DAG and majority of subspecies. This in turn modulated the phosphorylation of protein kinase C (PKC) isoforms PKCδ (Thr505), PKCµ (Ser744/748), and PKCα/βII (Thr638/641) and activity of the PKC‐mediated c‐Raf/MEK/ERK signaling cascade. A pan inhibitor of PKC (Go6983) blocked ERK1/2 activation by AKR1B10. In these cells, phospho‐p90RSK, phospho‐MSK, and Cyclin D1 expression was increased by AKR1B10, and pharmacological inhibition of the ERK signaling cascade with MEK1/2 inhibitors U0126 and PD98059 eradicated induction of phospho‐p90RSK, phospho‐MSK, and Cyclin D1. In breast cancer cells, AKR1B10 promoted the clonogenic growth and proliferation of breast cancer cells in two‐dimension (2D) and three‐dimension (3D) cultures and tumor growth in immunodeficient female nude mice through activation of the PKC/ERK pathway. These data suggest that AKR1B10 stimulates breast cancer cell growth and proliferation through activation of DAG‐mediated PKC/ERK signaling pathway.
Dynamic Privacy Leakage Analysis of Android Third-Party Libraries

Third-party libraries are widely used in Android apps. As third-party libraries share permissions with the host apps, they are easily over-privileged and leak users' privacy without notice. Combing static third-party library detection tool and dynamic Xposed framework, we propose a fine-grained and dynamic privacy leakage analysis tool to analyze the privacy leakage behaviors of third-party libraries in real time. This paper identifies three types of privacy leakage path inside apps. We evaluate 150 popular apps, collecting 1909 privacy information related call chains. We find the third-party libraries access to privacy information account for the largest proportion, and most of third-party libraries have direct network connections and the correspondent flows are inspected to validate the privacy leakage risk. The results show that the tool can achieve real-time, fine-grained and dynamic privacy behavior analysis of Android apps.