Miracle-dz/UniFAR-FTUs huggingface dataset:
Process-Oriented Diagnostics Principles, Practice, Community Development, and Common Standards

: Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.
MIT Open Access Articles On dispersion of compound DMCs

—Code for a compound discrete memoryless channel (DMC) is required to have small probability of error regardless of which channel in the collection perturbs the codewords. Capacity of the compound DMC has been derived classically: it equals the maximum (over input distributions) of the minimal (over channels in the collection) mutual information. In this paper the expression for the channel dispersion of the compound DMC is derived under certain regularity assumptions on the channel. Interestingly, dispersion is found to depend on a subtle interaction between the channels encoded in the geometric arrangement of the gradients of their mutual informations. It is also shown that the third-order term need not be logarithmic (unlike single-state DMCs). By a natural equivalence with compound DMC, all results (dispersion and bounds) carry over verbatim to a common message broadcast channel.
The Inﬂuence of Open versus Periodic Alongshore Boundaries on Circulation near Submarine Canyons

It is impractical to create gridded numerical models of coastal circulation with sufﬁcient resolution around small topographic features, such as submarine canyons, and still have the alongshore boundaries placed beyond the decay distance of coastal trapped waves. Two solutions to this problem are to make the alongshore boundaries either open or periodic. Numerical simulations were performed with upwelling and downwelling winds tocompare the effects of these different choices for boundary conditions. Several open boundary formulations were tried and three are discussed in detail. The offshore boundary was speciﬁed as ‘‘no gradient’’ for all variables with no serious effect. The ‘‘modiﬁed’’ Orlanski radiation condition is used for all variables at the alongshore boundaries, except the vertically integrated ﬂow that has the strongest effect on the model solution. An alongshore pressure gradient, opposing the wind, develops in the model if the modiﬁed Orlanski radiation condition is applied to the barotropic ﬂow, causing slower currents near the surface and deep undercurrents away from the shelf. The other cases, which combined either a radiation or a relaxation boundary condition with a local solution of the barotropic equations on the boundary, were at least initially similar to the periodic case but with slower alongshore ﬂow. The initial impact of these differences on the circulation within the canyon was small. The models with the open boundaries were more stable (did not develop strong ﬂow meanders) than the cases with periodic conditions as initial transients are not trapped, and ampliﬁed, within the domain. Thus, open cases, especially with the upwelling winds, could run for extended times.
Pumped-Storage Plant as a Good Complement for Wind and Solar Plants

— One of the main obstacles in wind and solar power penetration is intermittence. So to cope with this problem Pumped-Storage Plant (PSP) has been proposed as a good complement that can handle positive and negative imbalances. This paper, with the goal of imbalance cost minimization and profit maximization, proposes a stochastic model for optimal energy management. In this paper, the uncertainties related to the forecasted values for available output power of wind and solar units, imbalance market price and market price are modeled by a scenario-based stochastic programming. Scenarios, in the presented method, are generated by a roulette wheel mechanism based on probability distribution functions of the input random variables. Then in order to increase the optimization process speed, number of scenarios is decreased in a scenario reduction process. Finally the proposed offering model is compared with disjoint operations of wind, solar and pumped-storage and it has proved improvement and satisfactory results of joint operation profit.
Experimental optimization of a passive planar rhombic micromixer with obstacles for effective mixing in a short channel length

This paper presents the performance of a passive planar rhombic micromixer with diamond-shaped obstacles and a rectangular contraction between the rhombi. The device was experimentally optimized using water for high mixing efficiency and a low pressure drop over a wide range of Reynolds numbers (Re = 0.1–117.6) by varying geometrical parameters such as the number of rhombi, the distance between obstacles and the contraction width. Due to the large amount of data generated, statistical methods were used to facilitate and improve the results of the analysis. The results revealed a rank of factors influencing mixing efficiency: Reynolds number > number of rhombi > contraction width > inter-obstacles distance. The pressure drop measured after three rhombi depends mainly on Re and inter-obstacle distance. The resulting optimum geometry for the low Re regime has a contraction width of 101 μm and inter-obstacles distance of 93 μm, while for the high Re regime a contraction width of 400 μm and inter-obstacle distance of 121 μm are more appropriate. These mixers enabled 80% mixing efficiency creating a pressure drop of 6.0 Pa at Re = 0.1 and 5.1 × 104 Pa at Re = 117.6, with a mixer length of 2.5 mm. To the authors' knowledge, the developed mixer is one of the shortest planar passive micromixers reported to date.
Fixed Ipad Technology as an Innovation Idea in Chain Accommodation Businesses

In this study "Fixed iPad" technology is proposed as an innovative idea in chain accommodation businesses. The use of the proposed technology in accommodation businesses has been discussed and evaluated. In this study, the Diffusion of Innovations Theory is adopted. The idea of a “Fixed iPad” has been proposed to chain accommodation businesses. MAXQDA analysis program was used to visualize the data. The study showed that standards, suitability for the target, cost, and infrastructure are crucial determinants of innovation processes. It has been determined that chain accommodation enterprises cannot make decisions outside the standards. It has been determined that conducting R&D studies can be beneficial in innovation processes. In general, there is the opinion that the proposed innovation can have a positive effect on performance, satisfaction, and competition. A framework for the acceptance of innovations has been developed for chain accommodation businesses. This framework can be a prediction of innovation behavior toward chain accommodation businesses.
Quanti�cation of Urban Heat Intensity with Land Use/Land Cover Changes Using Landsat Satellite Data Over Urban Landscapes

11 Urban heat island (UHI) is a phenomenon which may have adverse effects on our environment and is 12 stimulated as a result of urbanisation or land cover changes. Thermal remote sensing has been beneficial for the 13 study of UHI effect. This paper analyses the variation in Land surface temperature (LST) with land cover 14 changes in Varanasi city of India from 1989 to 2018 using Landsat satellite images. A new index named Urban 15 Heat Intensity Ratio Index (UHIRI) was proposed to quantify the urban heat intensity from 1989 to 2018 which 16 was found to increase from 0.36 in year 1989 to 0.87 in year 2018. Further, contribution of each land cover 17 towards UHI was determined using Land cover contribution index (LCCI). The negative value of LCCI for 18 water and vegetation indicates its negative contribution towards UHI whereas positive value of LCCI for bare 19 soil and built-ups depicted its positive contribution towards UHI. The LCCI value for urban land cover shows 20 significant increase in 29 years i.e. 0.49, 1.43, 3.40, 4.37 for years 1989, 1997, 2008 and 2018 respectively. 21
REQUEST FOR PROPOSAL for CORROBORATIVE & WEIGHT-OF-EVIDENCE DEVELOPMENT AND ANALYSES

Submittal: Proposals must be received at the address below on or before Proposals received after the date and time stated above will not be accepted. Submissions must include: two (2) signed copies of Proposal delivered by mail or messenger to establish official receipt; one (1) unbound master suitable for black and white reproduction; and one (1) electronic copy (CD-ROM) of all submittal documents in Word or PDF format.
Recognition of Persian Digits from Zero to Nine using Acoustic Images based on Mel Capstrom Coefficients and Neural Network

— in this article, first, the database of zero to nine Persian digits have been recorded and collected using the voices of 50 men and women in the environment . In the proposed method, we first frame the preprocessed signal and then go through the improved window; in the next step, it enters the Fourier transform block . Now the Fourier transform spectrum is given to the Gaussian filter bank, and then the output power spectrum of the Gaussian bank filter is passed through Root Function, and then by applying cosine transform to compress the components, Mel-Capstrom coefficients are obtained . Finally, the acoustic image is formed as a matrix containing the temporal and frequency features of the speech signal using a two-dimensional inverse Fourier transform of the Mel Capstrom coefficient matrix . To classify and test the data, the features obtained are trained using an improved algorithm in the perceptron neural network with two hidden layers, and the recognition rate is reported at the end . The test results for the signal to different noises show the improvement of the noise signal detection rate by the proposed method, so that the recognition rate of the proposed algorithm without noise is 98.85.
Latin Morphology through the Centuries: Ensuring Consistency for Better Language Processing

This paper focuses on the process of harmonising the five Latin treebanks available in Universal Dependencies with respect to morphological annotation. We propose a workflow that allows to first spot inconsistencies and missing information, in order to detect to what extent the annotations differ, and then correct the retrieved bugs, with the goal of equalising the annotation of morphological features in the treebanks and producing more consistent linguistic data. Subsequently, we present some experiments carried out with UDPipe and Stanza in order to assess the impact of such harmonisation on parsing accuracy.
ASKPIR: Authorized Symmetric Keyword Privacy Information Retrieval Protocol Based on DID

Symmetric Private Information Retrieval (SPIR) is a stronger PIR protocol that ensures both client and server privacy. In many cases, the client needs authorization from the data subject before querying data. However, this also means that the server can learn the identity of the data subject. To solve such problems, we propose a new SPIR primitive, called authorized symmetric keyword information retrieval protocol (ASKPIR). Speciﬁcally, we designed an eﬃcient DID identiﬁcation algo-rithm based on the Pedersen Commitment, which is used to solve the identity management and privacy problems of data subject when data is shared by multiple parties in a distributed environment. Then, we present a novel authorization algorithm combining NIZK proof and DID, which can preserve client privacy. Finally, to improve the eﬃciency of client retrieval, our protocol constructs PSI-Payload with mqRPMT and OTE so as to support batch keyword searches. In addition, we provide a formal security analysis for the anonymity and unforgeability of the protocol and demonstrate that ASKPIR can achieve malicious security under the UC framework. Theoretical analysis and experimental results show that the ASKPIR protocol is more eﬃcient than other related works and solves the problem of incompatibility between data subject authorization and client privacy.
Chinese Patent Medicine Recommendation Algorithm Based on DPCNN-DeepFM

In this paper, we combine the embedded deep pyramid network and the deep FM recommendation model to complete the recommendation of proprietary Chinese medicines. Using real electronic medical records provided by Beijing University of Chinese Medicine and the Institute of Computer Science, Chinese Academy of Sciences as data sources; according to the patient’s main complaint, symptoms, tongue, pulse, age, gender, and other characteristics; using a deep pyramid network based on embedded patient feature fusion to predict the patient’s card Candidate categories, realize long-distance text association through text region embedding and fixed number of feature maps; and use deep FM model to process the sparse and dense features of the patient with the FM layer and the DNN layer separately, and finally real-time features and predictions for the patient The syndrome types are sorted. After comparative experiments and training, the AUC index is 78.90%, and the ACC value is 83.26%. Its overall performance is better than other RNN, CNN, and fast text network models. The experimental results show that the recommendation algorithm of Chinese patent medicine based on DPCNN-DeepFM has certain reference significance for the auxiliary clinical diagnosis of patients.
An Analysis on Spatiotemporal Variations of Soil and Vegetation Moisture from a 29 year Satellite Derived Dataset over Mainland Australia

[ 1 ] The spatiotemporal behavior of soil and vegetation moisture over mainland Australia was analyzed using passive microwave observations by four satellites going back to late 1978. Differences in measurement specifications prevented merging the data directly. A continuous product was developed for Australia by scaling percentiles of the cumulative moisture distribution within each grid cell to the percentiles of a reference sensor. The coefficient of correlation and root-mean-square error between rescaled values and the reference generally suggest good agreement. Using the merged data product, a strong El Nin˜o–Southern Oscillation signal in near-surface hydrology across Australia was confirmed. Spatial patterns of trends in annual averages show that western and northwestern Australia have experienced an increase in vegetation moisture content, while the east and southeast experienced a decrease. Soil moisture showed a similar spatial pattern but with larger regions experiencing a decrease. This could be explained by decreasing rainfall and increasing potential evapotranspiration during the extended winter period (May–September). The results give us reasonable confidence in the time series of soil and vegetation moisture derived by the scaling method developed in this study. Development of a global data set along these lines should enable better estimation of hydrological variables and should increase understanding of the impacts of ocean circulations on terrestrial hydrology and vegetation dynamics.
A time irreversible model of nucleotide substitution for the coronavirus evolution

SARS-CoV-2 is the cause of the worldwide epidemic of severe acute respiratory syndrome. Evolutionary studies of the virus genome will provide a predictor of the fate of COVID-19 in the near future. Recent studies of the virus genomes have shown that C to U substitutions are overrepresented in the genome sequences of SARS-CoV-2. Traditional time-reversible substitution models cannot be applied to the evolution of SARS-CoV-2 sequences. Therefore, in this study, I propose a new time-irreversible model and a new method for estimating the nucleotide substitution rate of SARS-CoV-2. Computer simulations showed that that the new method gives good estimates. I applied the new method to estimate nucleotide substitution rates of SARS-CoV-2 sequences. The result suggests that the rate of C to U substitution of SARS-Cov-2 is ten times higher than other types of substitutions.
Aberystwyth University Potential Benefits of Cattle Vaccination as a Supplementary Control for Bovine Tuberculosis

Vaccination for the control of bovine tuberculosis (bTB) in cattle is not currently used within any international control program, and is illegal within the EU. Candidate vaccines, based upon Mycobacterium bovis bacillus Calmette-Guérin (BCG) all interfere with the action of the tuberculin skin test, which is used to determine if animals, herds and countries are officially bTB-free. New diagnostic tests that Differentiate Infected from Vaccinated Animals (DIVA) offer the potential to introduce vaccination within existing eradication programs. We use within-herd transmission models estimated from historical data from Great Britain (GB) to explore the feasibility of such supplemental use of vaccination. The economic impact of bovine Tuberculosis for farmers is dominated by the costs associated with testing, and associated restrictions on animal movements. Farmers ’ willingness to adopt vaccination will require vaccination to not only reduce the burden of infection, but also the risk of restrictions being imposed. We find that, under the intensive sequence of testing in GB, it is the specificity of the DIVA test, rather than the sensitivity, that is the greatest barrier to see a herd level benefit of vaccination. The potential negative effects of vaccination could be mitigated through relaxation of testing. However, this could potentially increase the hidden burden of infection within Officially TB Free herds. Using our models, we explore the range of the DIVA test characteristics necessary to see a protective herd level benefit of vaccination. We estimate that a DIVA specificity
Potential plant species distribution in the Yellow River Delta under the influence of groundwater level and soil salinity

This article describes a multidisciplinary approach to assessing potential vegetation types. The relation between vegetation distribution as derived from field survey and habitat characteristics in the Yellow River Delta (YRD) was analyzed using detrended canonical correspondence analysis (DCCA). The three‐dimensional groundwater numerical simulation model MODFLOW yielded an accurate distribution of the shallow groundwater table within the study area. Groundwater table and soil salinity appeared to have the largest influence on the distribution patterns of specific indicator species. The quantitative relationships between species presence and environmental factors were further explored using logistic regression, allowing for the prediction of potential species distribution in relation to fluctuations in groundwater depth and soil salinity. Based on this, potential distribution maps for specific plant species and their communities were generated using ArcGIS. The potential vegetation map was compared to the actual vegetation map (interpreted from SPOT imagery), which leads to a discussion of the main factors responsible for fragmentation and degradation of the local vegetation system. Copyright © 2010 John Wiley & Sons, Ltd.
Distribution, chemical, and molecular composition of high and low molecular weight humic-like substances in ambient aerosols

Abstract. Humic-like substances (HULIS) encompass a continuum of molecular weight (MW) ranges, yet our understanding of how HULIS characteristics vary with MW is still limited and not well established. In this study, a combination of ultrafiltration and solid-phase extraction protocols was employed to fractionate the high MW (HMW; > 1 kDa) and low MW (LMW; < 1 kDa) HULIS fractions from ambient aerosols collected during summer and winter at a rural site. Subsequently, comprehensive characterization using total organic carbon, high-performance size exclusion chromatography (HPSEC), UV-visible (UV-vis) and fluorescence spectroscopy, Fourier transform infrared spectroscopy (FTIR), and negative electrospray ionization high-resolution mass spectrometry (ESI–HRMS) were conducted. The results revealed that HMW HULIS were dominated by larger-sized chromophores, substantially constituting a higher fraction of total organic carbon and UV absorption at 254 nm than LMW HULIS. While both HMW and LMW HULIS shared similar fluorophore types and functional groups, the former exhibited higher levels of humification and a greater presence of polar functional groups (e.g., −COOH; > C=O). HRMS analysis further unveiled that molecular formulas within HMW HULIS generally featured smaller sizes but higher degrees of unsaturation and aromaticity compared to those within LMW HULIS fractions. This observation suggests the possibility of small molecules assembling to form the HMW HULIS through intermolecular weak forces. Moreover, HMW HULIS contained a higher proportion of CHON but fewer CHO compounds than LMW HULIS. In both HMW and LMW HULIS, the unique molecular formulas were primarily characterized by lignin-like species, yet the former displayed a prevalence of N-enriched and highly aromatic species. Additionally, HMW HULIS contained more unique lipid-like compounds, while LMW HULIS exhibited a distinct presence of tannin-like compounds. These findings provide valuable insights into the distribution, optical properties, and molecular-level characteristics of HULIS in atmospheric aerosols, thereby advancing our understanding of their sources, composition, and environmental implications.
Federated Learning for Non-intrusive Load Monitoring

 Abstract —In the realm of non-intrusive load monitoring (NILM), extant deep learning approaches suffer from limitations including inadequate data samples, inadequate model generalization capacity, and insufficient safeguards for data privacy. To overcome these issues, this paper puts forward a novel NILM approach that leverages DeepAR to build a load monitoring model and incorporates federated learning and local fine-tuning methods to develop a non-intrusive load monitoring framework. Utilizing decentralized training, the proposed methodology facilitates iterative updates to model parameters through server-side aggregation, thereby enabling the collaborative construction of a monitoring model whilst maintaining strict confidentiality of individual customer data. The results of experiments conducted on the REDD dataset demonstrate that the approach outlined in this paper can markedly enhance the accuracy of load identification for frequently utilized electrical appliances.