Miracle-dz/UniFAR-FTUs huggingface dataset:
Power optimized variation aware dual-threshold SrAM cell design technique

: Bulk complementary metal-oxide semiconductor (CMOS) technology is facing enormous challenges at channel lengths below 45 nm, such as gate tunneling, device mismatch, random dopant fluctuations, and mobility degradation. Although multiple gate transistors and strained silicon devices overcome some of the bulk CMOS problems, it is sensible to look for revolutionary new materials and devices to replace silicon. It is obvious that future technology materials should exhibit higher mobility, better channel electrostatics, scalability, and robustness against process variations. Carbon nanotube-based technology is very promising because it has most of these desired features. There is a need to explore the potential of this emerging technology by designing circuits based on this technology and comparing their performance with that of existing bulk CMOS technology. In this paper, we propose a low-power variation-immune dual-threshold voltage carbon nanotube field effect transistor (CNFET)-based seven-transistor (7T) static random access memory (SRAM) cell. The proposed CNFET-based 7T SRAM cell offers ∼ 1.2 × improvement in standby power, ∼ 1.3 × improvement in read delay, and ∼ 1.1 × improvement in write delay. It offers narrower spread in write access time (1.4 × at optimum energy point [OEP] and 1.2 × at 1 V). It features 56.3% improvement in static noise margin and 40% improvement in read static noise margin. All the simulation measurements are taken at proposed OEP decided by the optimum results obtained after extensive simulation on HSPICE (high-performance simulation program with integrated circuit emphasis) environment. Nanotechnology, Science and Applications an international, peer- open on the science of nanotechnology in a wide range of industrial and academic applications. It is characterized by the rapid reporting across all sectors, including engi-neering, optics, bio-medicine, cosmetics, textiles, resource sustainability and science. Applied research into nano-materials, particles, nano- structures and fabrication, diagnostics and analytics, drug delivery and toxicology constitute the primary direction of the journal. The manuscript management system is completely online and includes a very quick and fair peer-review system, which is all easy to use.
MIT Open Access Articles Lightning: A Reconfigurable Photonic-Electronic SmartNIC for Fast and Energy-Efficient Inference

The massive growth of machine learning-based applications and the end of Moore’s law have created a pressing need to redesign computing platforms. We propose Lightning, the first reconfigurable photonic-electronic smartNIC to serve real-time deep neural network inference requests. Lightning uses a fast datapath to feed traffic from the NIC into the photonic domain without creating digital packet processing and data movement bottlenecks. To do so, Lightning leverages a novel reconfigurable count-action abstraction that keeps track of the required computation operations of each inference packet. Our count-action abstraction decouples the compute control plane from the data plane by counting the number of operations in each task and triggers the execution of the next task(s) without interrupting the dataflow. We evaluate Lightning’s performance using four platforms: a prototype, chip synthesis, emu-lations, and simulations. Our prototype demonstrates the feasibility of performing 8-bit photonic multiply-accumulate operations with 99.25% accuracy. To the best of our knowledge, our prototype is the highest-frequency photonic computing system, capable of serving real-time inference queries at 4.055 GHz end-to-end. Our simulations with large DNN models show that compared to Nvidia A100 GPU, A100X DPU, and Brainwave smartNIC, Lightning accelerates the average inference serve time by 337 × , 329 × , and 42 × , while consuming 352 × , 419 × , and 54 × less energy, respectively.
A Study of Weather-Image Classiﬁcation Combining VIT and a Dual Enhanced-Attention Module

: A weather-image-classiﬁcation model combining a VIT (vision transformer) and dual augmented attention module is proposed to address the problems of the insufﬁcient feature-extraction capability of traditional deep-learning methods with the recognition accuracy still to be improved and the limited types of weather phenomena existing in the dataset. A pre-trained model vision transformer is used to acquire the basic semantic feature representation of weather images. Dual augmented attention combined with convolutional self-attention and Atrous self-attention modules are used to acquire the low-level and high-level deep-image semantic representations, respectively, and the feature vectors are spliced and fed into the linear layer to obtain the weather types. Experimental validation is performed on the publicly available standard weather-image datasets MWD (Multi-class Weather Database) and WEAPD (Weather Phenomenon Database), and the two datasets are combined to enhance the comprehensiveness of the model for weather-phenomena recognition. The results show that the model achieves the highest F1 scores of 97.47%, 87.69% and 92.73% on the MWD, WEAPD and merged datasets, respectively. These scores are higher than the scores of recent deep-learning models with excellent performance in the experimental comparison, thereby, proving the effectiveness of the model.
Molecular Carcinogenesis

Department of GMU‐GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, China Department of Obstetrics, Obstetrics and Prenatal Diagnosis Center, Third Affiliated Hospital of Sun Yat‐Sen University, Guangzhou, China Department of Cancer Center, People’s Hospital of Baoan District, Shenzhen, China Department of Experimental Research, State Key Laboratory of Oncology in Southern China, Sun Yat‐sen University, Cancer Center, Guangzhou, China Department of Internal Medicine, Affiliated Cancer Hospital & Institute of Guangzhou Medical University, Guangzhou, China Department of Microsurgery, Trauma and Hand Surgery, First Affiliated Hospital of Sun Yat‐sen University, Guangzhou, China The Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia
Der Open-access-publikationsserver Der Zbw – Leibniz-informationszentrum Wirtschaft the Open Access Publication Server of the Zbw – Leibniz Information Centre for Economics Sleep Duration and Life Satisfaction Soeppapers on Multidisciplinary Panel Data Research Sleep Duration and Life Satisfaction S

Terms of use: The ZBW grants you, the user, the non-exclusive right to use the selected work free of charge, territorially unrestricted and within the time limit of the term of the property rights according to the terms specified at → http://www.econstor. eu/dspace/Nutzungsbedingungen By the first use of the selected work the user agrees and declares to comply with these terms of use. This series presents research findings based either directly on data from the German SocioEconomic Panel study (SOEP) or using SOEP data as part of an internationally comparable data set (e.g. CNEF, ECHP, LIS, LWS, CHER/PACO). SOEP is a truly multidisciplinary household panel study covering a wide range of social and The decision to publish a submission in SOEPpapers is made by a board of editors chosen by the DIW Berlin to represent the wide range of disciplines covered by SOEP. There is no external referee process and papers are either accepted or rejected without revision. Papers appear in this series as works in progress and may also appear elsewhere. They often represent preliminary studies and are circulated to encourage discussion. Citation of such a paper should account for its provisional character. A revised version may be requested from the author directly. Any opinions expressed in this series are those of the author(s) and not those of DIW Berlin. Research disseminated by DIW Berlin may include views on public policy issues, but the institute itself takes no institutional policy positions. Sleep is an important part of life, with an individual spending an estimated 32 years of her life asleep. Despite this importance, little is known about life satisfaction and sleep duration. Using German panel data, it is shown that sleep is an important factor for life satisfaction and that maximal life satisfaction is associated with about eight hours of sleep on a typical weekday. This figure represents, on average, an hour more than people currently sleep suggesting that more sleep would lead to a higher reported satisfaction with life. am grateful to Nick Adnett and Gerd Grözinger for useful comments and suggestions. The data used in this paper were made available by the German SocioEconomic Panel Study (SOEP) at the German Institute for Economic Research (DIW), Berlin. Further details about the SOEP are provided by Wagner et al. (2007). Neither the original collectors of the data nor the Archive bear any responsibility for the analyses or interpretations presented here. …
BLAISE PASCAL

We study linear rough diﬀerential equations and we solve perturbed linear rough diﬀerential equations using the Duhamel principle. These results provide us with a key technical point to study the regularity of the diﬀerential of the Itô map in a subsequent article. Also, the notion of linear rough diﬀerential equations leads to consider multiplicative functionals with values in Banach algebras more general than tensor algebras and to consider extensions of classical results such as the Magnus and the Chen-Strichartz formula.
Brush Management: Past Present, Future

It's coming again, the new collection that this site has. To complete your curiosity, we offer the favorite brush management past present future book as the choice today. This is a book that will show you even new to old thing. Forget it; it will be right for you. Well, when you are really dying of brush management past present future, just pick it. You know, this book is always making the fans to be dizzy if not to find.
Reconstructing long-term (1980-2022) daily ground particulate matter datasets in India (LongPMInd)

Severe airborne particulate matter (PM, including PM 2.5 and PM 10 ) pollution in India has caused widespread concern. Accurate PM datasets are fundamental for scientific policymaking and health impact assessment, while surface observations in India are limited due to scarce sites and uneven distribution. In this work, a simple structured, efficient, and robust model based on the Light Gradient Boosting Machine (LightGBM) was developed to fuse multi-source data and estimate long-term (1980-2022) historical daily ground PM datasets in India (LongPMInd). The LightGBM model shows good accuracy with out-20 of-sample, out-of-site, and out-of-year cross-validation CV test R 2 of 0.77, 0.70, and 0.66, respectively. Small performance gaps between PM 2.5 training and testing (delta RMSE of 1.06, 3.83, and 7.74 μg m -3 ) indicate low overfitting risks. With great generalization ability, the open-accessible, long-term, and high-quality daily PM 2.
Séminaire Laurent Schwartz EDP et applications

We report on the well-posedness of the Feynman problem for the Klein–Gordon equation on asymptotically Minkowski spacetimes. The main result is the invertibility of the Klein–Gordon operator with Feynman conditions at inﬁnite times. Furthermore, the inverse is shown to coincide with the Duistermaat–H¨ormander Feynman parametrix modulo smoothing terms.
Seismogenic faults, landslides, and associated tsunamis off southern Italy - Cruise No. M86/2 - December 27, 2011 - January 17, 2012 - Cartagena (Spain) - Brindisi (Italy)

The continental margins of southern Italy are located along converging plate boundaries, which are affected by intense seismicity and volcanic activity. Most of the coastal areas experienced severe earthquakes, landslides, and tsunamis in historical and/or modern times. The most prominent example is the Messina earthquake of Dec. 28, 1908 (Ms=7.3; 80,000 casualties), which was characterized by the worst tsunami Italy experienced in the historical time (~2000 casualties). It is, however, still unclear, whether this tsunami was triggered by a sudden vertical movement along a major fault during the earthquake or as a result of a giant marine slide initiated by the earthquake. The recurrence rates of major landslides and therefore the risk associated with landslides is also unknown. Based on detailed bathymetric data sets collected by Italian colleagues in the frame of the MaGIC Project (Marine Geohazards along the Italian Coast), we collected seismic data (2D and 3D) and gravity cores in three working areas (The Messina Straits, off Eastern Sicily, the Gioia Basin). A dense grid of new 2D-seismic data in the Messina Straits will allow to map fault patterns in great detail. One interesting outcome in this context is the identification of a set of normal faults striking in an EW-direction, which is almost perpendicular to the previously postulated faults. This EW-striking faults seem to be active. The area off eastern Sicily is characterized by numerous landslides and a complex deformation pattern. A 3D-seismic data set has been collected during the cruise using the so called P-cable in order to investigate these deformation patterns in detail. The new data will be the basis for a risk assessment in the working areas.
Plant necrotrophic bacterial disease resistance phenotypes, QTL, and metabolites identified through integrated genetic mapping and metabolomics in Solanum species

Most food crops are susceptible to necrotrophic bacteria that cause rotting and wilting diseases in fleshy organs and foods. All varieties of cultivated potato (Solanum tuberosum L.) are susceptible to diseases caused by Pectobacterium species, but resistance has been demonstrated in wild potato relatives including S. chacoense. Previous studies demonstrated that resistance is in part mediated by antivirulence activity of phytochemicals in stems and tubers. Little is known about the genetic basis of antivirulence traits, and the potential for inheritance and introgression into cultivated potato is unclear. Here, the metabolites and genetic loci associated with antivirulence traits in S. chacoense were elucidated by screening a sequenced S. tuberosum x S. chacoense recombinant inbred line (RIL) population for antivirulence traits of its metabolite extracts. Metabolite extracts from the RILs exhibited a quantitative distribution for two antivirulence traits that were positively correlated: quorum sensing inhibition and exo-protease inhibition, with some evidence of transgressive segregation, supporting the role of multiple loci and metabolites regulating these resistance-associated systems. Metabolomics was performed on the highly resistant and susceptible RILs that revealed 30 metabolites associated with resistance, including several alkaloids and terpenes. Specifically, several prenylated metabolites were more abundant in resistant RILs. We constructed a high-density linkage map with 795 SNPs mapped to 12 linkage groups, spanning a length of 1,507 cM and a density of 1 marker per 1.89 cM. Genetic mapping of the antivirulence and metabolite data identified five quantitative trait loci (QTLs) related to quorum sensing inhibition that explained 8-28% of the phenotypic variation and two QTLs for protease activity inhibition that explained 14-19% of the phenotypic variation. Several candidate genes including alkaloid, and secondary metabolite biosynthesis that are related to disease resistance were identified within these QTLs. Taken together, these data support that quorum sensing inhibition and exo-protease inhibition assays may serve as breeding targets to improve resistance to nectrotrophic bacterial pathogens in potato and other plants. The identified candidate genes and metabolites can be utilized in marker assisted selection and genomic selection to improve soft- rot and blackleg disease resistance.
The causal association between circulating cytokines with the risk of frailty and sarcopenia under the perspective of geroscience

Introduction Circulating cytokines were considered to play a critical role in the initiation and propagation of sarcopenia and frailty from observational studies. This study aimed to find the casual association between circulating cytokines and sarcopenia and frailty from a genetic perspective by two-sample Mendelian randomization (MR) analysis. Methods Data for 41 circulating cytokines were extracted from the genome-wide association study dataset of 8,293 European participants. Inverse-variance weighted (IVW) method, MR-Egger, and weighted median method were applied to assess the relationship of circulating cytokines with the risk of aging-related syndromes and frailty. Furthermore, MR-Egger regression was used to indicate the directional pleiotropy, and Cochran’s Q test was used to verify the potential heterogeneity. The “leave-one-out” method was applied to visualize whether there was a causal relationship affected by only one anomalous single-nucleotide polymorphisms. Results Genetic predisposition to increasing levels of interleukin-10 (IL-10), IL-12, and vascular endothelial growth factor (VEGF) was associated with the higher risk of low hand grip strength according to the IVW method [R = 1.05, 95% CI = 1.01–1.10, P = 0.028, false discovery rate (FDR)–adjusted P = 1.000; OR = 1.03, 95% CI = 1.00–1.07, P = 0.042, FDR-adjusted P = 0.784; OR = 1.02, 95% CI = 1.00–1.05, P = 0.038, FDR-adjusted P = 0.567]. Furthermore, genetically determined higher macrophage colony-stimulating factors (M-CSFs) were associated with a lower presence of appendicular lean mass (OR = 1.01, 95% CI = 1.00–1.02, P = 0.003, FDR-adjusted P = 0.103). Monokine induced by interferon-γ (MIG) and tumor necrosis factor–beta (TNF-β) were associated with a higher risk of frailty (OR = 1.03, 95% CI = 1.01–1.05, P < 0.0001, FDR-adjusted P = 0.012; OR = 1.01, 95% CI = 1.00–1.03, P = 0.013, FDR-adjusted P = 0.259). In this study, we did not find heterogeneity and horizontal pleiotropy between the circulating cytokines and the risk of frailty and sarcopenia. Conclusion Genetic predisposition to assess IL-10, IL-12, and VEGF levels was associated with a higher risk of low hand grip strength and M-CSF with the presence of appendicular lean mass. The high levels of TNF-β and MIG were associated with a higher risk of frailty. More studies will be required to explore the molecular biological mechanisms underlying the action of inflammatory factors.
Nonparametric Regression Analysis of BE4DBE2 Relationship with n and z Variables using Naive Bayes and SVM Classification on Nuclear Data

This research article describes several analyses of nuclear data using various statistical methods. The first analysis uses linear regression to investigate the relationship between the independent variables (n and z) and the response variable (BE4DBE2). The second analysis uses a nonparametric regression model to overcome the assumptions of normality and linearity in the data. The third analysis uses the Naive Bayes method to classify nuclear data based on variables n and z. The fourth analysis uses a decision tree to classify nuclear data based on the same variables. Finally, the article describes an SVM analysis and a K-means analysis to classify and group nuclide data. The article presents clear and organized descriptions of each analysis, including visual representations of the results. The findings of each analysis are discussed, providing valuable insights into the relationships between the variables and the response variable. The article demonstrates the usefulness of statistical methods in analyzing nuclear data.
EEG-based finger movement classification with intrinsic time-scale decomposition

Introduction Brain-computer interfaces (BCIs) are systems that acquire the brain's electrical activity and provide control of external devices. Since electroencephalography (EEG) is the simplest non-invasive method to capture the brain's electrical activity, EEG-based BCIs are very popular designs. Aside from classifying the extremity movements, recent BCI studies have focused on the accurate coding of the finger movements on the same hand through their classification by employing machine learning techniques. State-of-the-art studies were interested in coding five finger movements by neglecting the brain's idle case (i.e., the state that brain is not performing any mental tasks). This may easily cause more false positives and degrade the classification performances dramatically, thus, the performance of BCIs. This study aims to propose a more realistic system to decode the movements of five fingers and the no mental task (NoMT) case from EEG signals. Methods In this study, a novel praxis for feature extraction is utilized. Using Proper Rotational Components (PRCs) computed through Intrinsic Time Scale Decomposition (ITD), which has been successfully applied in different biomedical signals recently, features for classification are extracted. Subsequently, these features were applied to the inputs of well-known classifiers and their different implementations to discriminate between these six classes. The highest classifier performances obtained in both subject-independent and subject-dependent cases were reported. In addition, the ANOVA-based feature selection was examined to determine whether statistically significant features have an impact on the classifier performances or not. Results As a result, the Ensemble Learning classifier achieved the highest accuracy of 55.0% among the tested classifiers, and ANOVA-based feature selection increases the performance of classifiers on five-finger movement determination in EEG-based BCI systems. Discussion When compared with similar studies, proposed praxis achieved a modest yet significant improvement in classification performance although the number of classes was incremented by one (i.e., NoMT).
Recent progress in thin-film lithium niobate photonic crystal [Invited]

Lithium niobate is a material that exhibits outstanding electro-optic, nonlinear optical, acousto-optic, piezoelectric, photo-refractive, and pyroelectric properties. A thin-film lithium niobate photonic crystal can confine light in the sub-wavelength scale, which is beneficial to the integration of the lithium niobate on-chip device. The commercialization of the lithium niobate on insulator gives birth to the emergence of high-quality lithium niobate photonic crystals. In order to provide guidance to the research of lithium niobate photonic crystal devices, recent progress about fabrication, characterization, and applications of the thin-film lithium niobate photonic crystal is reviewed. The performance parameters of the different devices are compared.