Miracle-dz/UniFAR-FTUs huggingface dataset:
Variable impacts of contemporary versus legacy agricultural phosphorus on US river water quality

Significance Management of agricultural phosphorus (P) has been in effect for decades with limited improvements in downstream water quality. Accumulated legacy (historical) P sources can mobilize, serve as a continual nutrient source, and mask the effects of conservation efforts to improve water quality through reductions in contemporary agricultural inputs to surface waters. We used a proxy estimate of legacy sources and assessed if P lingering in soils long after application was a major contributor to river export. For most watersheds, contributions of legacy P to river export were small in comparison to contributions from contemporary surpluses (fertilizer + manure > crop uptake). Estimating the magnitude of contemporary versus legacy P sources provides critical information to support effective implementation of management plans. Phosphorus (P) fertilizer has contributed to the eutrophication of freshwater ecosystems. Watershed-based conservation programs aiming to reduce external P loading to surface waters have not resulted in significant water-quality improvements. One factor that can help explain the lack of water-quality response is remobilization of accumulated legacy (historical) P within the terrestrial-aquatic continuum, which can obscure the beneficial impacts of current conservation efforts. We examined how contemporary river P trends (between 1992 and 2012) responded to estimated changes in contemporary agricultural P balances [(fertilizer + manure inputs)—crop uptake and harvest removal] for 143 watersheds in the conterminous United States, while also developing a proxy estimate of legacy P contribution, which refers to anthropogenic P inputs before 1992. We concluded that legacy sources contributed to river export in 49 watersheds because mean contemporary river P export exceeded mean contemporary agricultural P balances. For the other 94 watersheds, agricultural P balances exceeded river P export, and our proxy estimate of legacy P was inconclusive. If legacy contributions occurred in these locations, they were likely small and dwarfed by contemporary P sources. Our continental-scale P mass balance results indicated that improved incentives and strategies are needed to promote the adoption of nutrient-conserving practices and reduce widespread contemporary P surpluses. However, a P surplus reduction is only 1 component of an effective nutrient plan as we found agricultural balances decreased in 91 watersheds with no consistent water-quality improvements, and balances increased in 52 watersheds with no consistent water-quality degradation.
Effect of Juice and Extracts from Saposhnikovia divaricata Root on the Colon Cancer Cells Caco-2

Colorectal cancer ranks 3rd in terms of cancer incidence. Growth and development of colon cancer cells may be affected by juice and extracts from Saposhnikovia divaricata root. The objective of the research was to analyze the effect of S. divaricata juice and extracts on the viability, membrane integrity and types of cell death of Caco-2 cells. Juice and extracts were analyzed using Ultra-High Performance Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and in respect of the presence of antioxidants, total carbohydrates, protein, fat and polyphenols. The contents of cimifugin β-D-glucopyranoside, cimifugin, 4′-O-glucopyranosyl-5-O-methylvisamminol, imperatorin and protein were the highest in juice. 50% Hydroethanolic extract had the greatest antioxidant potential, concentration of polyphenols and fat. Water extract was characterized by the highest content of glutathione. Juice and 75% hydroethanolic extract contained the most carbohydrates. After the application of juice, 50% extract and the juice fraction containing the molecules with molecular weights >50 kDa, a decrease of the cell viability was noted. Juice and this extract exhibited the protective properties in relation to the cell membranes and they induced apoptosis. The knowledge of further mechanisms of anticancer activity of the examined products will allow to consider their use as part of combination therapy.
Corilagin in Cancer: A Critical Evaluation of Anticancer Activities and Molecular Mechanisms

Corilagin (β-1-O-galloyl-3,6-(R)-hexahydroxydiphenoyl-d-glucose), an ellagitannin, is one of the major bioactive compounds present in various plants. Ellagitannins belong to the hydrolyzable tannins, a group of polyphenols. Corilagin shows broad-spectrum biological, and therapeutic activities, such as antioxidant, anti-inflammatory, hepatoprotective, and antitumor actions. Natural compounds possessing antitumor activities have attracted significant attention for treatment of cancer. Corilagin has shown inhibitory activity against the growth of numerous cancer cells by prompting cell cycle arrest at the G2/M phase and augmented apoptosis. Corilagin-induced apoptosis and autophagic cell death depends on production of intracellular reactive oxygen species in breast cancer cell line. It blocks the activation of both the canonical Smad and non-canonical extracellular-signal-regulated kinase/Akt (protein kinase B) pathways. The potential apoptotic action of corilagin is mediated by altered expression of procaspase-3, procaspase-8, procaspase-9, poly (ADP ribose) polymerase, and Bcl-2 Bax. In nude mice, corilagin suppressed cholangiocarcinoma growth and downregulated the expression of Notch1 and mammalian target of rapamycin. The aim of this review is to summarize the anticancer efficacy of corilagin with an emphasis on the molecular mechanisms involving various signaling pathways in tumor cells.
Transcutaneous Sonography for Detection of the Cervical Vagus Nerve

Cervical vagus nerve is not identified by computed tomography or magnetic resonance imaging. Transcutaneous sonography may be the best imaging study to evaluate the cervical vagus nerve. A 7 to 18 MHz linear array transducer was placed transversely on the lateral neck focusing on the carotid sheath from the clavicle level upward to the digastric muscle level bilaterally. The gray-scale technique was used, with the scan setting for the thyroid gland. Between January 2015 and March 2016, 314 patients with 628 cervical vagus nerves were enrolled, including 104 men and 210 women. Their ages ranged from 14 to 84 years. Transcutaneous sonography identified the entire trunk of bilateral cervical vagus nerves in 254 (80.9%) patients and did not identify 1 or both cervical vagus nerves in the other 60 (19.1%) patients. Among 628 cervical vagus nerves, transcutaneous sonography identified 626 (99.6%) lower cervical vagus nerves and 551 (87.7%) upper cervical vagus nerves. Among 551 visible upper cervical vagus nerves, 495 (89.8%) nerves were located laterally, 17 (3%) nerves were located medially, 9 (1.6%) nerves were located anteriorly, and 30 (5.4%) nerves were located posterior to the internal carotid artery. Man and left-side nerve were the factors associated with the anatomical variation in the upper cervical vagus nerve. Transcutaneous sonography can be the best imaging study to show the cervical vagus nerve and may be helpful to evaluate the nerve before neck operation.
Gender and Psychological Well-Being

Background: Research has consistently reported gender differences in mental health, but studies on differences in psychological well-being between women and men have not yielded conclusive results. The aim of this study was to examine the relevance of gender to the psychological well-being of adult individuals. A cross-sectional study with a sample of 1700 men and 1700 women from the general Spanish population was conducted. Their ages ranged from 21 to 64 years, and they were assessed with Ryff’s Psychological Well-Being Scales and the Bem Sex Role Inventory. Results: Men scored higher than women in self-acceptance and autonomy, and women scored higher than men in personal growth and positive relations with others. The most relevant variable in the psychological well-being of both women and men was high masculinity. Other relevant variables in women’s well-being were high femininity, not having a manual occupation, not being homemakers, and professional occupation. Men´s well-being also was higher in professional men and in men with a skilled non-manual occupation, men with high femininity and men who were not single, divorced or widowed. Conclusions: Adherence to traditional gender roles is relevant to the psychological well-being of women and men, and women and men whose self-concept includes both masculine-instrumental and feminine-expressive characteristics have greater well-being.
Characterization of the ERß-|- mouse heart

Although the heart responds to estrogen, it is not clear whether estrogen acts directly on heart muscle or indirectly by means of the vascular, immune, or nervous system. No role for estrogen receptor (ER) in the heart has been established, but ER / mice are hypertensive, and as they age, their hearts become enlarged. Histological and ultrastructural analysis of the heart revealed a disarray of myocytes, a disruption of intercalated discs, an increase in the number and size of gap junctions, and a profound alteration in nuclear structure, concomitantly with a loss of expression of lamin A C from the nuclear envelope. In the lungs of ER / mice, lamin A C was located in the nuclear membrane, indicating that lamin A C is not an ER -regulated gene. Immunohistochemical studies with ER antibodies failed to detect ER in the myocardium. We conclude that abnormalities in heart morphology in ER / mice are likely due to stress on the nuclear envelope as a result of the chronic sustained systolic and diastolic hypertension observed in ER / mice. Because neither ER nor ER could be detected in heart muscle, the effects of estrogen on the myocardium seem to be indirect.
Age attenuates the transcriptional changes that occur with sleep in the medial prefrontal cortex

Sleep abnormalities are common with aging. Studies show that sleep plays important roles in brain functions, and loss of sleep is associated with increased risks for neurological diseases. Here, we used RNA sequencing to explore effects of age on transcriptome changes between sleep and sleep deprivation (SD) in medial prefrontal cortex and found that transcriptional changes with sleep are attenuated in old. In particular, old mice showed a 30% reduction in the number of genes significantly altered between sleep/wake and, in general, had smaller magnitudes of changes in differentially expressed genes compared to young mice. Gene ontology analysis revealed differential age effects on certain pathways. Compared to young mice, many of the wake‐active functions were similarly induced by SD in old mice, whereas many of the sleep‐active pathways were attenuated in old mice. We found similar magnitude of changes in synaptic homeostasis genes (Fos, Arc, and Bdnf) induced by SD, suggesting intact synaptic upscaling on the transcript level during extended wakefulness with aging. However, sleep‐activated processes, such as DNA repair, synaptogenesis, and axon guidance, were sensitive to the effect of aging. Old mice expressed elevated levels of immune response genes when compared to young mice, and enrichment analysis using cell‐type‐specific markers indicated upregulation of microglia and oligodendrocyte genes in old mice. Moreover, gene sets of the two cell types showed age‐specific sleep/wake regulation. Ultimately, this study enhances understanding of the transcriptional changes with sleep and aging, providing potential molecular targets for future studies of age‐related sleep abnormalities and neurological disorders.
Time-Frequency Methodology for Newborn Electroencephalographic Seizure Detection

Techniques previously designed for electroencephalographic (EEG) seizure detection in the newborn have been relatively inefficient due to their incorrect assumption of local stationarity of the EEG. To overcome the problem raised by the proven nonstationarity of the EEG signal, current methods are extended to a time–frequency (TF) approach [8, 10]. This allows the analysis and characterization of the different newborn EEG patterns, the first step toward an automatic TF seizure detection and classification. An in-depth analysis of the previously proposed autocorrelation and spectrum seizure detection techniques identified the detection criteria that can be readily extended to the TF domain. We present the various patterns of observed TF seizure signals and relate them to current specialist knowledge of seizures. In particular, initial results indicate that a quasilinear instantaneous frequency (IF) can be used as a critical feature of the EEG seizure characteristics. These findings led to propose a TF-based seizure detector. This detector performs a two-dimensional (2D) correction between the EEG signal and a reference template selected as a model of the EEG seizure in TF domain.
On Understanding Knowledge Graph Representation

Many methods have been developed to represent knowledge graph data, which implicitly exploit low-rank latent structure in the data to encode known information and enable unknown facts to be inferred. To predict whether a relationship holds between entities, their embeddings are typically compared in the latent space following a relation-specific mapping. Whilst link prediction has steadily improved, the latent structure, and hence why such models capture semantic information, remains unexplained. We build on recent theoretical interpretation of word embeddings as a basis to consider an explicit structure for representations of relations between entities. For identifiable relation types, we are able to predict properties and justify the relative performance of leading knowledge graph representation methods, including their often overlooked ability to make independent predictions.
Scale-Equivariant Neural Networks with Decomposed Convolutional Filters

Encoding the input scale information explicitly into the representation learned by a convolutional neural network (CNN) is beneficial for many vision tasks especially when dealing with multiscale input signals. We study, in this paper, a scale-equivariant CNN architecture with joint convolutions across the space and the scaling group, which is shown to be both sufficient and necessary to achieve scale-equivariant representations. To reduce the model complexity and computational burden, we decompose the convolutional filters under two pre-fixed separable bases and truncate the expansion to low-frequency components. A further benefit of the truncated filter expansion is the improved deformation robustness of the equivariant representation. Numerical experiments demonstrate that the proposed scale-equivariant neural network with decomposed convolutional filters (ScDCFNet) achieves significantly improved performance in multiscale image classification and better interpretability than regular CNNs at a reduced model size.
Motion Estimation in Occupancy Grid Maps in Stationary Settings Using Recurrent Neural Networks

In this work, we tackle the problem of modeling the vehicle environment as dynamic occupancy grid map in complex urban scenarios using recurrent neural networks. Dynamic occupancy grid maps represent the scene in a bird’s eye view, where each grid cell contains the occupancy prob-ability and the two dimensional velocity. As input data, our approach relies on measurement grid maps, which contain occupancy probabilities, generated with lidar measurements. Given this configuration, we propose a recurrent neural net-work architecture to predict a dynamic occupancy grid map, i.e. filtered occupancy and velocity of each cell, by using a sequence of measurement grid maps. Our network architecture contains convolutional long-short term memories in order to sequentially process the input, makes use of spatial context, and captures motion. In the evaluation, we quantify improvements in estimating the velocity of braking and turning vehicles compared to the state-of-the-art. Additionally, we demonstrate that our approach provides more consistent velocity estimates for dynamic objects, as well as, less erroneous velocity estimates in static area.
Scalable and Efficient Data Authentication for Decentralized Systems

Decentralized systems such as blockchains promise to fundamentally change how untrusted parties exchange data and assets. A key challenge in the decentralized setting is scalably authenticating data in the system. Merkle Patricia trees (MPT) are widely used in decentralized systems like Ethereum, to verify that the data is correct and up-to-date. Unfortunately, MPTs incur significant overhead due to random IO operations, serialization, and hashing. This paper presents the Distributed Merkle Patrica Tree (DMPT), a novel data structure that reduces the overheads of the MPT. A DMPT vertically shards the MPT across the memory of multiple nodes, eliminating the IO bottleneck. DMPTs reduce network bandwidth utilization using a combination of novel techniques such as witness compaction and node bagging. Compared to the MPT used in Ethereum, put and get operations in the DMPT achieve 80-160x better throughput, even when the Ethereum MPT is stored in memory. We demonstrate the effectiveness of DMPT by building FVCHAIN (Fast Verification blockchain), a modified version of Ethereum which uses DMPT instead of MPT. In a four-region geo-distributed deployment, FVCHAIN can verify 20,000 transactions per second (20x higher than Ethereum).
Improved Summation from Shuffling

A protocol by Ishai et al.\ (FOCS 2006) showing how to implement distributed $n$-party summation from secure shuffling has regained relevance in the context of the recently proposed \emph{shuffle model} of differential privacy, as it allows to attain the accuracy levels of the curator model at a moderate communication cost. To achieve statistical security $2^{-\sigma}$, the protocol by Ishai et al.\ requires the number of messages sent by each party to {\em grow} logarithmically with $n$ as $O(\log n + \sigma)$. In this note we give an improved analysis achieving a dependency of the form $O(1+\sigma/\log n)$. Conceptually, this addresses the intuitive question left open by Ishai et al.\ of whether the shuffling step in their protocol provides a "hiding in the crowd" amplification effect as $n$ increases. From a practical perspective, our analysis provides explicit constants and shows, for example, that the method of Ishai et al.\ applied to summation of $32$-bit numbers from $n=10^4$ parties sending $12$ messages each provides statistical security $2^{-40}$.
Long Short-Term Memory Neural Networks for False Information Attack Detection in Software-Defined In-Vehicle Network.

A modern vehicle contains many electronic control units (ECUs), which communicate with each other through the in-vehicle network to ensure vehicle safety and performance. Emerging Connected and Automated Vehicles (CAVs) will have more ECUs and coupling between them due to the vast array of additional sensors, advanced driving features and Vehicle-to-Everything (V2X) connectivity. Due to the connectivity, CAVs will be more vulnerable to remote attackers. In this study, we developed a software-defined in-vehicle Ethernet networking system that provides security against false information attacks. We then created an attack model and attack datasets for false information attacks on brake-related ECUs. After analyzing the attack dataset, we found that the features of the dataset are time-series that have sequential variation patterns. Therefore, we subsequently developed a long short term memory (LSTM) neural network based false information attack/anomaly detection model for the real-time detection of anomalies within the in-vehicle network. This attack detection model can detect false information with an accuracy, precision and recall of 95%, 95% and 87%, respectively, while satisfying the real-time communication and computational requirements.
FALCON: Fast and Lightweight Convolution for Compressing and Accelerating CNN

How can we efficiently compress Convolutional Neural Networks (CNN) while retaining their accuracy on classification tasks? A promising direction is based on depthwise separable convolution which replaces a standard convolution with a depthwise convolution and a pointwise convolution. However, previous works based on depthwise separable convolution are limited since 1) they are mostly heuristic approaches without a precise understanding of their relations to standard convolution, and 2) their accuracies do not match that of the standard convolution. In this paper, we propose FALCON, an accurate and lightweight method for compressing CNN. FALCON is derived by interpreting existing convolution methods based on depthwise separable convolution using EHP, our proposed mathematical formulation to approximate the standard convolution kernel. Such interpretation leads to developing a generalized version rank-k FALCON which further improves the accuracy while sacrificing a bit of compression and computation reduction rates. In addition, we propose FALCON-branch by fitting FALCON into the previous state-of-the-art convolution unit ShuffleUnitV2 which gives even better accuracy. Experiments show that FALCON and FALCON-branch outperform 1) existing methods based on depthwise separable convolution and 2) standard CNN models by up to 8x compression and 8x computation reduction while ensuring similar accuracy. We also demonstrate that rank-k FALCON provides even better accuracy than standard convolution in many cases, while using a smaller number of parameters and floating-point operations.
The Converse Envelope Theorem

I prove an envelope theorem with a converse: the envelope formula is equivalent to a first‐order condition. Like Milgrom and Segal's (2002) envelope theorem, my result requires no structure on the choice set. I use the converse envelope theorem to extend to general outcomes and preferences the canonical result in mechanism design that any increasing allocation is implementable, and apply this to selling information.
Disconnection-Mediated Twin Embryo Growth in Mg

While deformation twinning in hexagonal close-packed metals has been widely studied due to its substantial impact on mechanical properties, an understanding of the detailed atomic processes associated with twin embryo growth is still lacking. Conducting molecular dynamics simulations on Mg, we show that the propagation of twinning disconnections emitted by basal-prismatic interfaces controls the twin boundary motion and is the rate-limiting mechanism during the initial growth of the twin embryo. The time needed for disconnection propagation is related to the distance between the twin tips, with widely spaced twin tips requiring more time for a unit twin boundary migration event to be completed. Thus, a phenomenological model, which unifies the two processes of disconnection and twin tip propagation, is proposed here to provide a quantitative analysis of twin embryo growth. The model fits the simulation data well, with two key parameters (twin tip velocity and twinning disconnection velocity) being extracted. In addition, a linear relationship between the ratio of twinning disconnection velocity to twin tip velocity and the applied shear stress is observed. Using an example of twin growth in a nanoscale single crystal from the recent literature, we find that our molecular dynamics simulations and analytical model are in good agreement with experimental data.