Miracle-dz/UniFAR-FTUs huggingface dataset:
Economic Valuation and Pricing of Inertia in Inverter-Dominated Power Systems

This paper studies the procurement and pricing of inertial response using a frequency-constrained unit commitment formulation, which co-optimizes the provision of energy and inertia services while accounting for their complementary properties. The proposed approach builds on a two-step process that allows to differentiate between the units being online for energy purposes and the ones committed additionally solely for inertia provision. Subsequently, three novel pricing and payment schemes that reimburse inertia providers in a transparent and fair manner according to their individual participation are proposed. The analysis considers both synchronous and converter-based generators and provides insights regarding the impact of each pricing scheme on total system cost, as well as on the investment signals for technologies capable of offering affordable inertial response. The results show that all three methods will have a beneficial impact on frequency stability and aid the operator in ensuring system reliability, whereas the policy implications to different inertia providing units will vary between the payment schemes.
Spoof Face Detection Via Semi-Supervised Adversarial Training

Face spoofing causes severe security threats in face recognition systems. The previous anti-spoofing mainly focused on supervised techniques, typically with either binary or auxiliary supervision. Most of them have to ‘see’ both spoofing face data and live face data during training to realize the task of face anti-spoofing. In this paper, we propose a semi-supervised adversarial learning framework for spoof face detection, which largely relaxes the supervision condition. To capture the underlying structure of live face data in latent representation space, we propose to train the live face data only, with a convolutional Encoder-Decoder network acting as a Generator, and a second convolutional network serving as a Discriminator. The generator and discriminator are trained by competing with each other while collaborating to understand the live faces. Since the spoof face detection is video-based (i.e., temporal information), we intuitively take the optical flow maps converted from consecutive video frames as input. Our approach is free of the spoof faces, thus being robust and general to different types of face spoofing (even unknown spoofing). Experiments on cross-dataset tests show that our semi-supervised method achieves better or comparable results to state-of-the-art supervised techniques. We also conduct ablation studies for the proposed method.
Point2Mesh

In this paper, we introduce Point2Mesh, a technique for reconstructing a surface mesh from an input point cloud. Instead of explicitly specifying a prior that encodes the expected shape properties, the prior is defined automatically using the input point cloud, which we refer to as a self-prior. The self-prior encapsulates reoccurring geometric repetitions from a single shape within the weights of a deep neural network. We optimize the network weights to deform an initial mesh to shrink-wrap a single input point cloud. This explicitly considers the entire reconstructed shape, since shared local kernels are calculated to fit the overall object. The convolutional kernels are optimized globally across the entire shape, which inherently encourages local-scale geometric self-similarity across the shape surface. We show that shrink-wrapping a point cloud with a self-prior converges to a desirable solution; compared to a prescribed smoothness prior, which often becomes trapped in undesirable local minima. While the performance of traditional reconstruction approaches degrades in non-ideal conditions that are often present in real world scanning, i.e., unoriented normals, noise and missing (low density) parts, Point2Mesh is robust to non-ideal conditions. We demonstrate the performance of Point2Mesh on a large variety of shapes with varying complexity.
Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso

Inverse‐probability‐weighted estimators are the oldest and potentially most commonly used class of procedures for the estimation of causal effects. By adjusting for selection biases via a weighting mechanism, these procedures estimate an effect of interest by constructing a pseudopopulation in which selection biases are eliminated. Despite their ease of use, these estimators require the correct specification of a model for the weighting mechanism, are known to be inefficient, and suffer from the curse of dimensionality. We propose a class of nonparametric inverse‐probability‐weighted estimators in which the weighting mechanism is estimated via undersmoothing of the highly adaptive lasso, a nonparametric regression function proven to converge at nearly n−1/3$ n^{-1/3}$ ‐rate to the true weighting mechanism. We demonstrate that our estimators are asymptotically linear with variance converging to the nonparametric efficiency bound. Unlike doubly robust estimators, our procedures require neither derivation of the efficient influence function nor specification of the conditional outcome model. Our theoretical developments have broad implications for the construction of efficient inverse‐probability‐weighted estimators in large statistical models and a variety of problem settings. We assess the practical performance of our estimators in simulation studies and demonstrate use of our proposed methodology with data from a large‐scale epidemiologic study.
QuIS: The Question of Intelligent Site Selection

Site selection is one of the most important decisions to be made by companies. Such a decision depends on various factors of sites, including socio-economic, geographical, ecological, as well as specific requirements of companies. The existing approaches for site selection are manual, subjective, and not scalable. The paper presents the new approach QuIS for site selection, which is automatic, scalable, and more effective than existing state-of-the-art methods. It impartially finds suitables site based on analyzing decisive data of all location factors in both time and space. Another highlight of the proposed method is that the recommendations are supported by explanations, i.e., why something was suggested. To assess the effectiveness of the presented method, a case study on site selection of supermarkets in Germany is performed using real data of more than 200 location factors for 11.162 sites. Evaluation results show that there is a big coverage (86.4 %) between the sites of existing supermarkets selected by economists and the sites recommended by the presented method. In addition, the method also recommends many sites (328) where it is benefial to open a new supermarket. Furthermore, new decisive location factors are revealed, which have an impact on the existence of supermarkets.
An online convex optimization algorithm for controlling linear systems with state and input constraints

This paper studies the problem of controlling linear dynamical systems subject to point-wise-in-time constraints. We present an algorithm similar to online gradient descent, that can handle time-varying and a priori unknown convex cost functions while restraining the system states and inputs to polytopic constraint sets. Analysis of the algorithm's performance, measured by dynamic regret, reveals that sub-linear regret is achieved if the variation of the cost functions is sublinear in time. Finally, we present an example to illustrate implementation details as well as the algorithm's performance and show that the proposed algorithm ensures constraint satisfaction.
Leaf pubescence mediates intraguild predation between predatory mites

Plant morphological traits such as leaf pubescence may affect herbivores and their natural enemies at the individual, population and community levels. Leaf pubescence has been repeatedly shown to mediate predator-herbivore interactions whereas the influence of leaf pubescence on predator-predator interactions such as intraguild predation (IGP) has seldom been investigated. Using a three-pronged approach we assessed the influence of leaf pubescence on the predatory mites Kampimodromus aberrans and Euseius finlandicus. Both predators occur on broad-leaved trees in Europe. Euseius finlandicus is mostly found on trees with glabrous leaves whereas K. aberrans mainly occurs on trees with pubescent leaves. We hypothesized that leaf pubescence mediates IGP between K. aberrans and E. finlandicus and thereby determines their dominance and proportional abundance. A field survey on apple revealed that the abundance of K. aberrans and E. finlandicus is negatively correlated, with the former predominating on cultivars with strongly pubescent leaves and the latter predominating on cultivars with little pubescent or glabrous leaves. Microhabitat choice tests showed that K. aberrans preferentially resides on pubescent leaves whereas E. finlandicus preferentially resides on glabrous leaves. The effects of leaf pubescence on survival and development of immature IG predators and IG prey were reversed for K. aberrans and E. finlandicus. In the presence of the IG predator E. finlandicus, immature K. aberrans had higher survival probabilities on pubescent leaves than on glabrous ones. In contrast, the survival chances of immature E. finlandicus were higher on glabrous leaves than on pubescent ones when the IG predator K. aberrans was present. Artificial leaf pubescence enhanced IG prey capture by immature K. aberrans and prolonged their longevity but impaired IG prey capture by immature E. finlandicus and shortened their longevity. We conclude that leaf pubescence mediates IGP strength and symmetry and discuss the implications to natural and biological control.
Cost-Aware Robust Tree Ensembles for Security Applications

Features of security classifiers have various costs to be manipulated. The costs are asymmetric across features and to the directions of changes, which cannot be precisely captured by existing cost models based on $L_p$-norm robustness. In this paper, we utilize such domain knowledge to increase the evasion cost against security classifiers, specifically, tree ensemble models that are widely used by security tasks. We propose a new cost modeling method to capture the domain knowledge of features as constraint, and then we integrate the cost-driven constraint into the node construction process to train robust tree ensembles. During the training process, we use the constraint to find data points that are likely to be perturbed given the costs of the features, and we optimize the quality of the trees using a new robust training algorithm. Our cost-aware training method can be applied to different types of tree ensembles, including random forest model that cannot be robustly trained by previous methods. Using twitter spam detection as the security application, our evaluation results show that training cost-aware robust model can rank high cost features as the most important ones, and increase the adaptive attack cost by 6.4X compared to the baseline. Our code is available at this https URL.
Phytoremediation in Wetland Ecosystems: Progress, Problems, and Potential

Assessing the phytoremediation potential of wetlands is complex due to variable conditions of hydrology, soil/sediment types, plant species diversity, growing season, and water chemistry. Conclusions about long-term phytoremediation potential are further complicated by the process of ecological succession in wetlands. This review of wetlands phytoremediation addresses the role of wetland plants in reducing contaminant loads in water and sediments, including metals; volatile organic compounds (VOC), pesticides, and other organohalogens; TNT and other explosives; and petroleum hydrocarbons and additives. The review focuses on natural wetland conditions and does not attempt to review constructed wetland technologies. Physico-chemical properties of wetlands provide many positive attributes for remediating contaminants. The expansive rhizosphere of wetland herbaceous shrub and tree species provides an enriched culture zone for microbes involved in degradation. Redox conditions in most wetland soil/sediment zones enhance degradation pathways requiring reducing conditions. However, heterogeneity complicates generalizations within and between systems. Wetland phytoremediation studies have mainly involved laboratory microcosm and mesocosm technologies, with the exception of planted poplar communities. Fewer large-scale field studies have addressed remediation actions by natural wetland communities. Laboratory findings are encouraging with regards to phytoextraction and degradation by rhizosphere and plant tissue enzymes. However, the next phase in advancing the acceptance of phytoremediation as a regulatory alternative must demonstrate sustained contaminant removal by intact natural wetland ecosystems.
Mycorrhizal chronosequence near Exit Glacier, Alaska

Mycorrhizal fungi associated with plant species may change as vegetation develops following disturbance. The objectives of this study were to compare ectomycorrhizae through a chronosequence on deglaciated land from bare mineral soil to mature forest and to determine time required for mycorrhizal formation on natural seedlings. A chronosequence that formed as Exit Glacier retreated enabled us to document changes in mycorrhizae on existing woody plants, including Populus balsamifera ssp. trichocarpa (Torr. & Gray) Hult, (black cottonwood) that dominates the early stages, Alnus sinuata (Regel) Rydb. (Sitka alder) that has few ectomycorrhizal fungal associates, and Picea sitchensis (Bong.) Carr. (Sitka spruce) that typifies late successional stages. Some seedlings of Populus balsamifera became ectomycorrhizal within 3 weeks of germination but most took longer. Although a dark type without clamp connections dominated willows in the second and third stage, it was not a dominant in the first stage and was rare .
Espécies de Syrphidae (Diptera) visitantes das flores de Eryngium horridum (Apiaceae) no Vale do Rio Pardo, RS, Brasil

No periodo entre dezembro de 2001 a dezembro de 2003, realizaram-se coletas com rede entomologica de insetos visitantes das flores de Eryngium horridum (Apiaceae) na Regiao do Vale do Rio Pardo, RS, Brasil. Esta planta e perene, frequente em campos secos e apresenta expressiva dispersao. Possui, no Rio Grande do Sul, epoca de floracao entre novembro e janeiro. Foram capturados 1.066 insetos visitantes, destes, 569 Syrphidae. Identificaram-se 60 especies de Syrphidae, distribuidas em 16 generos. O genero Palpada Macquart, 1834 foi dominante, e Ornidia Lepeletier & Serville, 1828 e Toxomerus Macquart, 1855 abundantes. Das especies mais frequentes, Palpada furcata (Wiedemann, 1819) ocupou posicao mais elevada. Os sirfideos apresentaram preferencia pelas temperaturas entre 28 e 32oC, e foram mais frequentemente coletados entre as 10 e 14 horas, com picos entre as 10 e 11 horas. As femeas foram as mais frequentes. O predominio de sirfideos robustos e mais ageis sobre sirfideos de menor porte como Toxomerus e Allograpta Osten Sacken, 1875, pode ter sido resultante de competicao interespecifica. Eristalinus taeniops (Wiedemann, 1818) e pela primeira vez citada para o Estado do Rio Grande do Sul. A alta diversidade e abundância dos especimes coletados nas flores de E. horridum sao indicadores da importância desta na dieta dos sirfideos, visto que possui grande numero de inflorescencias e floracao ocorrendo nos meses de baixa oferta de recursos alimentares na area de estudo.
Rapid Field Assessment of Organic Pollution with a Family-Level Biotic Index

Tolerance values for families of arthropods are presented to enable calculation of a family-level biotic index (FBI) in the field. In six streams differing in substrates and degree of organic pollution, an average of 23 min, 35 s was needed to assess the condition of a stream in the field using the FBI; this period was at least an hour less than is normally required to evaluate a stream with the generic- and species-level biotic index (BI). Comparison of the FBI and BI of replicated samples from these six streams and from 120 random samples from other Wisconsin streams showed that some accuracy is lost by using the FBI, with the FBI usually indicating greater pollution than the BI in unpolluted or slightly polluted streams and less pollution in polluted streams. The purpose of the FBI is to provide a rapid, but less critical, evaluation of streams in the field by biologists who can recognize arthropod families by sight. It is not intended as a substitute for the BI.
Influence of high energy supplements containing fatty acids on the productivity of pasture-fed dairy cows

Three groups of 8 cows in their second month of lactation grazed irrigated perennial pasture alone, or grazed and were supplemented with either 3.3 kg/day of a high energy supplement or 3.8 kg of a high energy supplement containing additional long-chain fatty acids. Yields of milk and milk products were generally highest for those cows fed the supplement containing fat. Yield of milk fat was 13% higher in fat supplemented cows than those in the other supplemented treatment because these cows overcame the negative effect of starch supplements on milk fat test. Inclusion of long-chain fatty acids in the diet caused only minor changes in the fatty acid composition of the milk fat and in the various rumen parameters. The immediate marginal increases in daily yields of milk and milk fat per kg of long-chain fatty acids consumed by cows were 1.8 and 0.33 kg/cow. After comparison with data from other experiments, we concluded that the type of basal diet is not an important factor influencing the response of dairy cows to dietary long-chain fatty acids
Phenotypic and genetic parameters of body composition traits and flesh colour in Atlantic salmon, Salmo salar L

Data obtained on 3.5-year-old offspring of 58 sires and 171 dams (two year classes) of Atlantic salmon, Salmo salar L. , were analysed. A substantial effect of sexual maturation status was demonstrated for several body composition traits, most pronounced for the content of fat and dry matter of muscle. Maturation effects generally exceeded estimated sex effects. Intermediate estimates of heritability (0.20-0.30) derived from the sire component of variance were obtained for intestinal fat weight, intestinal fat index, dressing percentage and fat and dry matter content of muscle. Corresponding parameters of the subjectively scored traits belly flap constitution, amount of intestinal fat and flesh colour were all low (= 0.10). Heritabilities derived from the sire and dam components of variance were generally similar in magnitude, indicating the absence of non-additive genetic and environmental effects common to full-sibs. Viewed in the context of likely selection goals for commercial breeding schemes, the results did not reveal major adverse genetic relationships among the investigated traits. However, the estimated genetic correlations of muscle fat with body weight (0.42 ± 0.17) and intestinal fat index (-0.64 ± 0.19) may be unfavourable.
Predictors of misconceptions, knowledge, attitudes, and practices of COVID-19 pandemic among a sample of Saudi population

Objectives: To explore the predictors of misconceptions, knowledge, attitudes, and practices of the COVID-19 pandemic among a sample of the Saudi population and its impact. Design: An online cross-sectional study. Setting: Jeddah, Saudi Arabia. Participants: A total of 2006 participants [953(47.5%) females, and 1053(52.5%) males], and more than 18 years of age were included in the study. Data collection and analysis: This cross-sectional survey was conducted at the Faculty of Medicine, Rabigh, King Abdulaziz University (KAU). The participants were approached by social media (SM). An online questionnaire was administered, and the data were analyzed on SPSS-26. Results: The SM was the leading source of information 889(43.9%). Two-thirds of the participants, 1250(66.9%) had various misconceptions, and about one-third of the study participants 637(31.7%) had disturbed social, mental, and psychological wellbeing, and many participants became more religious. Two-thirds of the study participants, 1292(68.1%) had good knowledge score. The attitude was highly positive in 1867(93.1%) participants, and the practice score was adequate in 1939(97.7%). The participants educational status was the predictor of good knowledge. Male gender and divorced ones were the predictor of poor practice scores and age 51-60 years, private jobholders, and students were the predictors of the good practice scores. The Saudi nationality was the predictor of participants positive attitude, while the male gender and divorced ones were predictors of a negative attitude. The male gender and higher education status were the predictors of good concepts, while the older age and job (own business) were the predictors of misconceptions. Conclusion: Our study observed several predictors of misconceptions, knowledge, attitudes, and practices among the Saudi population. Our participants had a good realization of the impact of this pandemic.
Properties of polyphenol oxidase obtained from Musa acuminata × balbisiana Colla cv. “Pisang Awak” pulp and peel Propiedades de polifenoloxidasa obtenido de la pulpa y piel de Musa acuminata × balbisiana Colla cv. “Pisang Awak”

The characteristics of crude polyphenol oxidase (PPO) extracted from the peel and pulp of the plantain Awak (Musa acuminata × balbisiana) were investigated to provide useful information on the plantain during processing operations. The optimum pH-activity of crude PPO for the peel and pulp is 5.5 and 6.5, respectively. Optimum temperature-activity for the peel and pulp was 30 °C. The K m and V max of the crude PPO peel were 4.92 mM and 0.702 Abs/min, respectively, while the K m and V max for the crude PPO pulp were 3.77 mM and 0.513 Abs/min, respectively. Crude PPO from both peel and pulp exhibited similar trends in thermostability. Crude Awak PPO from peel and pulp was indicated to be 100% inhibited by 1 mM of l-cysteine, ascorbic acid, and sodium metabisulphite. Citric acid was found to be moderately effective for PPO inhibition, and NaCl was demonstrated to be a weak inhibitor. Las características de las polifenoloxidasa (PFO) extraídas de la piel y pulpa sin refinar del plátano Awak (Musa acuminata × balbisiana) fueron investigadas para obtener información útil sobre el plátano durante las operaciones de procesado. El pH óptimo para PFO de la piel y pulpa es 5,5 y 6,5, respectivamente. La temperatura óptima para la piel y pulpa fue 30 °C. Las K m y V max de las PFO de piel sin refinar fueron 4,92 mM y 0,702 Abs/min, respectivamente, mientras las K m y V max de las PFO de pulpa sin refinar fueron 3,77 mM y 0,513 Abs/min, respectivamente. Las PFO de ambas piel y pulpa mostraron tendencias similares en termoestabilidad. Las PFO de piel y pulpa sin refinar de Awak resultaron ser 100% inhibidas por 1 mM de l-cisteína, ácido ascórbico y metabisulfito de sodio. El ácido cítrico se mostró moderadamente efectivo para inhibición de PFO y se demostró que NaCl es un inhibidor débil.