Miracle-dz/UniFAR-FTUs huggingface dataset:
Do Auto-Regressive Models Protect Privacy? Inferring Fine-Grained Energy Consumption From Aggregated Model Parameters

We investigate the extent to which statistical predictive models leak information about their training data. More specifically, based on the use case of household (electrical) energy consumption, we evaluate whether white-box access to auto-regressive (AR) models trained on such data together with background information, such as household energy data aggregates (e.g., monthly billing information) and publicly-available weather data, can lead to inferring fine-grained energy data of any particular household. We construct two adversarial models aiming to infer fine-grained energy consumption patterns. Both threat models use monthly billing information of target households. The second adversary has access to the AR model for a cluster of households containing the target household. Using two real-world energy datasets, we demonstrate that this adversary can apply maximum a posteriori estimation to reconstruct daily consumption of target households with significantly lower error than the first adversary, which serves as a baseline. Such fine-grained data can essentially expose private information, such as occupancy levels. Finally, we use differential privacy (DP) to alleviate the privacy concerns of the adversary in dis-aggregating energy data. Our evaluations show that differentially private model parameters offer strong privacy protection against the adversary with moderate utility, captured in terms of model fitness to the cluster.
Dynamic Ride-Hailing with Electric Vehicles

We consider the problem of an operator controlling a fleet of electric vehicles for use in a ride-hailing service. The operator, seeking to maximize profit, must assign vehicles to requests as they arise as well as recharge and reposition vehicles in anticipation of future requests. To solve this problem, we employ deep reinforcement learning, developing policies whose decision making uses [Formula: see text]-value approximations learned by deep neural networks. We compare these policies against a reoptimization-based policy and against dual bounds on the value of an optimal policy, including the value of an optimal policy with perfect information, which we establish using a Benders-based decomposition. We assess performance on instances derived from real data for the island of Manhattan in New York City. We find that, across instances of varying size, our best policy trained with deep reinforcement learning outperforms the reoptimization approach. We also provide evidence that this policy may be effectively scaled and deployed on larger instances without retraining.
Host traits and evolution shape key coral-bacterial symbioses

The success of tropical scleractinian corals depends on their ability to establish symbioses with microbial partners. Host traits and evolution are known to shape the coral microbiome, but to what extent they affect its composition remains unclear. Here, by using twelve coral species representing the complex and robust clades, we show that functional traits and host evolutionary history explain 14% of the tissue and 13% of the skeletal microbiome composition, providing evidence that these predictors contribute to shaping the holobiont in terms of the presence and abundance of key bacterial species. Additionally, our study shows that the coral tissue and skeleton are dominated by rare bacteria and the skeleton can function as a microbial reservoir. Together, we provide novel insights into the processes driving coral-bacterial symbioses along with an improved understanding of the scleractinian tissue and skeleton microbiome.
X-Ray Detection of Transient Spin Accumulation on Cu atoms near a Co/Cu Interface

R. Kukreja, 2, ∗ S. Bonetti, 3 Z. Chen, 3 D. Backes, Y. Acremann, J. Katine, A.D. Kent, H. A. Dürr, H. Ohldag, and J. Stöhr † SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025, USA Department of Materials Science and Engineering, Stanford University, CA 94305, USA Department of Physics, Stanford University, CA 94305, USA Physics Department, New York University, 4 Washington Place, New York, NY 10003, USA Laboratorium für Festkörperphysik, ETH Zürich, HPF C 5, Otto-Stern-Weg 1, Zürich 8093, Switzerland HGST, a Western Digital Company, 3403 Yerba Buena Road, San Jose, CA 95135, USA
Multitime Scale Active and Reactive Power Coordinated Optimal Dispatch in Active Distribution Network Considering Multiple Correlation of Renewable Energy Sources

To improve the adaptability for renewable energy sources (RES), a multitime scale optimal dispatch method, which considers the multiple correlations of RES, is proposed in the active distribution network (ADN). The proposed method includes a multiple correlation model of RES and a scheduling framework. The multiple correlation model of RES is formulated by t Copula function, Sklar's theorem, and conditional distribution of multivariate t distribution. The multiple correlation model can estimate the forecast error of the future period according to the historical data and the latest prediction. The scheduling framework further employs the revised forecast to coordinate the fast/slow-response regulation resources in the ADN under three timescales. In the day-ahead stage, the operation state of slow-response resources is optimized and determined. In the intraday stage, the output of the fast-response resource, which is transferred to the real-time stage as reference trajectory, is optimized based on the short-term prediction. In the real-time stage, the stochastic model predictive control is adopted to adjust the output of fast-response resources based on ultra-short-term prediction and reference trajectory. Case analyses indicate that the proposed method can effectively reduce the voltage fluctuation, promote the utilization of demand-side resources, and improve the system economic performance by introducing the multiple correlation model.
How Music Awakens the Heart: An Experimental Study on Music, Emotions, and Connectedness

ABSTRACT Many studies in the field of positive media psychology have investigated the effects of meaningful film on viewer’s feelings and openness to others, all the while music is the number #1 media source for feeling moved, touched or inspired. Therefore, the current study examined the role of meaningful compared to pleasurable music on listeners emotional experiences, feelings of connectedness, and altruistic behaviors. In a pre-posttest experiment, 105 participants (M age = 23.800; SD = 6.082; 77.3% female) listened to either their favorite meaningful music or their favorite pleasurable music. Findings revealed that listening to meaningful music leads to stronger feelings of being moved, having a lump in one’s throat and tears crying, more contemplation, a stronger motivation to seek what matters in life, and a stronger desire to express love to close others, compared to listening to pleasurable music. Both listening to meaningful and pleasurable music were found to lead to a wide range of intense and blended emotions, a desire to connect to others, and same levels of altruism. In sum, meaningful and pleasurable music can evoke a different mix of emotions, however, both are strong and open our hearts to others.
ESRA: Explainable Scientific Research Assistant

We introduce Explainable Scientific Research Assistant (ESRA), a literature discovery platform that augments search results with relevant details and explanations, aiding users in understanding more about their queries and the returned papers beyond existing literature search systems. Enabled by a knowledge graph we extracted from abstracts of 23k papers on the arXiv’s cs.CL category, ESRA provides three main features: explanation (for why a paper is returned to the user), list of facts (that are relevant to the query), and graph visualization (drawing connections between the query and each paper with surrounding related entities). The experimental results with humans involved show that ESRA can accelerate the users’ search process with paper explanations and helps them better explore the landscape of the topics of interest by exploiting the underlying knowledge graph. We provide the ESRA web application at http://esra.cp. eng.chula. ac.th/.
Siliceous and non‐nutritious: Nitrogen limitation increases anti‐herbivore silicon defences in a model grass

Silicon (Si) accumulation alleviates a diverse array of environmental stresses in many plants, including conferring physical resistance against insect herbivores. It has been hypothesised that grasses, in particular, utilise ‘low metabolic cost’ Si for structural and defensive roles under nutrient limitation. While carbon (C) concentrations often negatively correlate with Si concentrations, the relationship between nitrogen (N) status and Si is more variable. Moreover, the impacts of N limitation on constitutive physical Si defences (e.g. silica and prickle cells) against herbivores are unknown. We determined how N limitation affected Si deposition in the model grass Brachypodium distachyon and how changes in these constitutive defences impacted insect herbivore Helicoverpa armigera growth rates. We used scanning electron microscopy (SEM) and energy dispersive X‐ray spectrometry in conjunction with X‐ray mapping (XRM) to quantify physical structures on leaves and determine Si deposition patterns. We also determined how N limitation and Si supply impacted the jasmonic acid (JA) pathway, the master regulator of induced defences against arthropod herbivores. N limitation reduced shoot growth by over 40%, but increased root mass (+21%), leaf Si concentrations (+50%) and the density of silica (+28%) and flattened prickle (+76%) cells. Energy‐dispersive X‐ray spectroscopy and XRM established that Si was being deposited in these structures, together with hooked prickle cells and macro‐hairs. Herbivore relative growth rates (RGR) were more than 115% lower in Si‐supplied plants compared to plants without Si supply and negatively correlated with leaf Si concentration and silica cell density. RGR was further reduced by N limitation and positively correlated with leaf N concentrations. Increases in JA concentrations following induction of the JA pathway were at least doubled by N limitation. Synthesis. Si accumulation and deposition were highly regulated by N availability, with N limitation promoting both constitutive Si physical defences and induction of the JA defensive pathway, in line with the resource availability hypothesis. These results indicate that grasses use ‘low‐cost Si’ when resources are limited and suggest that plant productivity may benefit from optimising conventional fertilisers and Si fertilisation.
Fixed-Time Third-Order Super-Twisting-like Sliding Mode Motion Control for Piezoelectric Nanopositioning Stage

This paper presents a novel third-order super-twisting-like integral sliding mode controller (3-ISMC) for trajectory tracking of nanopositioning applications. Different from traditional sliding mode control methods presenting with chattering problems, the proposed approach provides continuous control inputs, which brings much convenience for practical applications. Moreover, the fixed-time convergence of the proposed 3-ISMC is guaranteed independently of initial conditions. The estimation of the fixed convergence time and stability are derived based on the Lyapunov method. Simulation results demonstrate that the proposed controller exhibits chattering free and quick transient response performance for a piezoelectric nanopositioning system under model uncertainties and external disturbances.
Lipid-Glycoadjuvant@AuNPs Inhibits Tumor Gowth and Regulates Tumor Microenvironments by Tumor-Specific CTL-Ferived IFNγ

Inducing tumor-specific T cell responses and regulating suppressive tumor microenvironments have been a challenge for effective tumor therapy. CpG (ODN), the Toll-like receptor 9 agonist, has been widely used as adjuvants of cancer vaccines to induce T cell responses. However, clinical benefits of CpG based tumor vaccine were limited primarily due to the poor targeting to lymph nodes. Here we developed a lipid-glycoadjuvant@AuNPs (LCpG) by covalent conjugation of CpG with lipid-glycopolymers, which could be rapidly transported to and retained longer in the lymphoid nodes than unmodified CpG. In melanoma model, LCpG controlled both primary tumor and its metastasis, and established long-term memory. In spleen and tumor draining lymphoid nodes, LCpG activated tumor-specific Tc1 responses, with increased CD8+ T-cell proliferation, antigen–specific Tc1 cytokine production and specific-tumor killing capacity. In tumor microenvironments, antigen-specific Tc1 induced by the LCpG promoted CTL infiltration, skewed tumor associated macrophages to M1 phenotype, inhibited Treg differentiation and induced proinflammatory cytokines production in a CTL-derived IFN-γ-dependent manner. In vivo cell depletion and adoptive transfer experiments confirmed that antitumor activity of LCpG included vaccine was mainly dependent on CTL-derived IFN-γ. The anti-tumor efficacy of LCpG was dramatically enhanced when combined with anti-PD1 immunotherapy. Together, our results demonstrated that LCpG was a promising adjuvant for vaccine formulation which could augment tumor-specific Tc1 activity, and regulate tumor microenvironments.
Efeito do crédito do BNDES para a geração de empregos agroindustriais no Brasil

Resumo: No Brasil, o credito publico tem papel relevante no apoio as empresas, em especial aquelas pertencentes ao setor industrial. Nesse sentido, este estudo tem por objetivo realizar uma avaliacao do impacto dos desembolsos do Banco Nacional de Desenvolvimento Economico e Social (BNDES) na geracao de empregos na agroindustria brasileira. Para tanto, utilizaram-se microdados da Relacao Anual de Informacoes Sociais (RAIS) e do BNDES no âmbito empresarial. As tecnicas econometricas empregadas foram Propensity Score Matching (PSM) e Diferencas em Diferencas (DID). Foram tomados como referencia os periodos pre e pos-expansao dos desembolsos do BNDES, em virtude da politica anticiclica adotada pelo governo em 2009, para conter os impactos da crise internacional deflagrada em 2008. Os resultados encontrados apontam que, para a amostra em analise, empresas financiadas entre 2009 e 2010, o impacto no crescimento do emprego foi estatisticamente significativo e as empresas que receberam credito do BNDES apresentaram dinâmica diferenciada em termos de geracao de emprego. Tais resultados evidenciam que a ampliacao da politica de desembolsos do BNDES consistiu em um instrumento importante sobre a geracao de emprego em empresas pertencentes a agroindustria.
Boundary-Oriented Binary Building Segmentation Model With Two Scheme Learning for Aerial Images

Various deep learning-based segmentation models have been developed to segment buildings in aerial images. However, the segmentation maps predicted by the conventional convolutional neural network-based methods cannot accurately determine the shapes and boundaries of segmented buildings. In this article, to improve the prediction accuracy for the boundaries and shapes of segmented buildings in aerial images, we propose the boundary-oriented binary building segmentation model (B3SM). To construct the B3SM for boundary-enhanced semantic segmentation, we present two-scheme learning (Schemes I and II), which uses the upsampling interpolation method (USIM) as a new operator and a boundary-oriented loss function (B-Loss). In Scheme I, a raw input image is processed and transformed into a presegmented map. In Scheme II, the presegmented map from Scheme I is transformed into a more fine-grained representation. To connect these two schemes, we use the USIM operator. In addition, the novel B-Loss function is implemented in B3SM to extract the features of the boundaries of buildings effectively. To perform quantitative evaluation of the shapes and boundaries of segmented buildings generated by B3SM, we develop a new metric called the boundary-oriented intersection over union (B-IoU). After evaluating the effectiveness of two-scheme learning, USIM, and B-Loss for building segmentation, we compare the performance of B3SM to those of other state-of-the-art methods using public and custom datasets. The experimental results demonstrate that the B3SM outperforms other state-of-the-art models, resulting in more accurate shapes and boundaries for segmented buildings in aerial images.
Migration, reactivity, and sulfur tolerance of copper species in SAPO-34 zeolite toward NOx reduction with ammonia

Cu/SAPO-34 catalysts were prepared by wet impregnation and ion-exchange methods, and both the catalysts were hydrothermally treated at 750 °C in 10 vol% H2O/air for 24 h. Subsequently, the as-received and hydrothermally treated catalysts were exposed to a sulfur poisoning treatment at 350 °C in 100 ppm SO2/10 vol% H2O/air for 24 h and examined for NOx conversion. Sulfur poisoning considerably decreased the NOx conversion efficiency of the catalysts at low temperatures. In contrast, it improved the high-temperature selective catalytic reduction (SCR) activities of the as-received catalysts. The ion-exchange-prepared catalysts displayed higher sulfur tolerance than the impregnation-prepared catalysts at 150–350 °C. The electron paramagnetic resonance, X-ray photoelectron spectroscopy, energy-dispersive X-ray spectroscopy and H2-temperature-programmed reduction results showed that sulfur poisoning significantly influenced the migration of the copper species and thereby the amount of active isolated Cu2+. More dispersed CuSO4 was produced on the ion-exchange-prepared catalysts than on the impregnation-prepared catalysts after sulfur poisoning. The dispersed CuSO4 showed considerably higher SCR activity than the crystalline CuSO4. Both the dispersed CuSO4 and remaining isolated Cu2+ determined the low-temperature SCR behavior of the sulfur-poisoned catalysts.
Diel cycle in a farmland bird is shaped by contrasting predation and human pressures

In human-dominated landscapes, human disturbances may contrast (spatially and/or temporally) with risk imposed by non-human predators. However, how prey adjust behaviour to minimize risk from multiple threats remains unclear. In Central-Western France, we investigated patterns of activity, space and habitat use, and causes of variations during the diel cycle of the grey partridge (captive-reared, released), a farmland bird facing multiple risks (nocturnal predation, diurnal hunting pressure). We also investigated influence of individual space use, relative to risk-related features on the fate of birds. Birds adjusted their behaviours in ways consistent with the reduction of risk from nocturnal carnivores at night and hunters during daytime. We recorded bimodal crepuscular activity, likely explained by commuting movements between spatially-separated diurnal and nocturnal sites composed of different habitats: selection of open terrains and avoidance of predator reservoirs at night vs. use of high-vegetation cover during daytime. We observed space use differences between surviving, hunted and predated birds. Predation and hunting activities act as contrasting pressures, selecting birds based on their spatial behaviour, which has likely shaped diel adjustments at the population level. An improved consideration of temporal variation in environmental pressures would help to reliably address factors constraining populations, so increasing wildlife management efficiency.
Extraction of Citric Acid and Maleic Acid from Their Aqueous Solutions Using a Phosphorus-Bonded Extractant, Tri-n-octylphosphineoxide, and a Secondary Amine, Dioctylamine

The aim of this study is to investigate the extraction of citric acid and maleic acid from their aqueous solutions using different solvent–extractant mixtures in order to find the most effective composition for the extraction. Citric and maleic acids are chosen as the carboxylic acids due to their commercial worth in the industrial processes. Carboxylic acids are recovered from their aqueous solutions by reactive extraction, a promising liquid–liquid extraction technique, using trioctylphosphineoxide (TOPO), and a secondary amine called dioctylamine (DOA). TOPO has been chosen as an extractant since it has low water solubility, high stability, and it is more environmentally friendly than the amine-type extractants. For other amine extractants used in reactive extraction processes, there is a lack of study in the literature about the extraction of these acids with DOA. Extractants were dissolved in nine different solvents (butanol, decanol, octanol, isoamylalcohol, octane, decane, methylisobutylketone, and.
Robust recognition technique for handwritten Kannada character recognition using capsule networks

Automated reading of handwritten Kannada documents is highly challenging due to the presence of vowels, consonants and its modifiers. The variable nature of handwriting styles aggravates the complexity of machine based reading of handwritten vowels and consonants. In this paper, our investigation is inclined towards design of a deep convolution network with capsule and routing layers to efficiently recognize Kannada handwritten characters. Capsule network architecture is built of an input layer, two convolution layers, primary capsule, routing capsule layers followed by tri-level dense convolution layer and an output layer. For experimentation, datasets are collected from more than 100 users for creation of training data samples of about 7769 comprising of 49 classes. Test samples of all the 49 classes are again collected separately from 3 to 5 users creating a total of 245 samples for novel patterns. It is inferred from performance evaluation; a loss of 0.66% is obtained in the classification process and for 43 classes precision of 100% is achieved with an accuracy of 99%. An average accuracy of 95% is achieved for all remaining 6 classes with an average precision of 89%.
Upper Mantle Hydration Indicated by Decreased Shear Velocity Near the Southern Mariana Trench From Rayleigh Wave Tomography

Reduction of seismic velocities has been employed to study the hydration of incoming plates and forearc mantle in recent years. However, few constraints have been obtained in the Southern Mariana Trench. We use an ocean bottom seismograph (OBS) deployment to conduct Rayleigh wave tomographic studies to derive the SV‐wave velocity structure near the Southern Mariana Trench. Measured group and phase velocities as a function of period are inverted to determine the SV‐wave velocity using a Bayesian Monte Carlo algorithm. The incoming Pacific Plate is characterized by low velocities (3.6–4.1 km/s) within the upper ∼25 km of the mantle near the trench, indicating extensive mantle hydration of the incoming plate in southern Mariana. The velocity reduction in the forearc mantle is not as large as in central Mariana, most likely indicating a lower forearc serpentinization in this region, which is consistent with the absence of serpentinite mud volcanoes.