Miracle-dz/UniFAR-FTUs huggingface dataset:
Symmetric inclusion process with slow boundary: Hydrodynamics and hydrostatics

We study the hydrodynamic and hydrostatic limits of the one-dimensional open symmetric inclusion process with slow boundary. Depending on the value of the parameter tuning the interaction rate of the bulk of the system with the boundary, we obtain a linear heat equation with either Dirichlet, Robin or Neumann boundary conditions as hydrodynamic equation. In our approach, we combine duality and first-second class particle techniques to reduce the scaling limit of the inclusion process to the limiting behavior of a single, non-interacting, particle.
Analysis of Mathematical Problem-Solving Skills and Student Process Skills in Problem-Based Learning

This study aims to (1) determine the characteristics of mathematics learning with problem-based learning in the 2013 curriculum, and 2) describe mathematical problem-solving abilities and student process skills in learning with the problem-based learning model. This type of research is a mixed method research with the concurrent embedded design which is a combination of qualitative and quantitative research methods that are carried out together. In this study, qualitative research is the primary method while quantitative research is a secondary method. The research subjects were 37 students of MTs PB Roudlotul Mubtadiin Balekambang Jepara. Student process skills observed include observing, questioning, gathering information, associating, and forming networks / communicating. The results of this study indicate (1) the learning device with the problem-based learning model in the 2013 curriculum is effective because it meets the completeness test in the experimental class and the comparative test that the experimental class mathematical problemsolving ability is better than the control class mathematical problem-solving ability, (2) score students ' problem-solving ability in the experimental class increased after following the learning with the problem-based learning model and the students' process skills in following the learning in the 2013 curriculum increased significantly.
Understanding Multi-Modal Perception Using Behavioral Cloning for Peg-In-a-Hole Insertion Tasks

One of the main challenges in peg-in-a-hole (PiH) insertion tasks is in handling the uncertainty in the location of the target hole. In order to address it, high-dimensional sensor inputs from sensor modalities such as vision, force/torque sensing, and proprioception can be combined to learn control policies that are robust to this uncertainty in the target pose. Whereas deep learning has shown success in recognizing objects and making decisions with high-dimensional inputs, the learning procedure might damage the robot when applying directly trial- and-error algorithms on the real system. At the same time, learning from Demonstration (LfD) methods have been shown to achieve compelling performance in real robotic systems by leveraging demonstration data provided by experts. In this paper, we investigate the merits of multiple sensor modalities such as vision, force/torque sensors, and proprioception when combined to learn a controller for real world assembly operation tasks using LfD techniques. The study is limited to PiH insertions; we plan to extend the study to more experiments in the future. Additionally, we propose a multi-step-ahead loss function to improve the performance of the behavioral cloning method. Experimental results on a real manipulator support our findings, and show the effectiveness of the proposed loss function.
Heterotic strings on homogeneous spaces

We construct heterotic string backgrounds corresponding to families of homogeneous spaces as exact conformal field theories. They contain left cosets of compact groups by their maximal tori supported by NS‐NS 2‐forms and gauge field fluxes. We give the general formalism and modular‐invariant partition functions, then we consider some examples such as SU (2)/U (1) ~ S2 (already described in a previous paper) and the SU (3)/U(1)2 flag space. As an application we construct new supersymmetric string vacua with magnetic fluxes and a linear dilaton.
Weighted Meyers estimates in perforated domains

The present work aims to provide Meyers estimates throughout a finer inner regularity theory in perforated domains. We also provide a hypercontractivity property on correctors whenever the perforations are controlled with a uniformly bounded random variable and the underlying probability space admits a weaker form of ergodicity which we called coarsened logarithmic Sobolev inequality.
Towards understanding physical origin of 2175 Å extinction bump in interstellar medium

The 2175 A ultraviolet (UV) extinction bump in interstellar medium (ISM) of the Milky Way was discovered in 1965. After intensive exploration of more than a half century, however, its exact origin still remains a big conundrum that is being debated. Here we propose a mixture model by which the extinction bump in ISM is argued possibly relevant to the clusters of hydrogenated T-carbon (HTC) molecules (C40H16) that have intrinsically a sharp absorption peak at the wavelength 2175 A. By linearly combining the calculated absorption spectra of HTC mixtures, graphite, MgSiO3 and Fe2SiO4, we show that the UV extinction curves of optional six stars can be nicely fitted. This present work poses an alternative explanation toward understanding the physical origin of the 2175 A extinction bump in ISM of the Milky Way.
Multivariate L\'evy-type drift change detection with unknown post-change parameter and mortality modeling

In this paper, using Bayesian approach, we solve the quickest drift change detection problem for a multidimensional L\'evy process consisting of both a continuous gaussian part and a jump component. We allow a general a priori distribution of the change point as well as random post-change drift parameter. Classically, our optimality criterion is based on a probability of false alarm and an expected delay of the detection. The main technique uses the optimal stopping theory and is based on solving a certain free-boundary value problem. The paper is supplemented by an extensive numerical analysis related with the construction of the Generalized Shiryaev-Roberts statistic applied to analysis of Polish life tables (after proper calibration) and predicting the joint drift change in the correlated force of mortality of men and women.
Optimum Nitrogen Fertilization of Cool‐Season Grasses in the Northeast USA

Many studies have looked at the economically optimum N application rate (cost of N vs. increased yield) for cool-season forage grasses, but few of these studies have also addressed the effect of N fertilization on livestock or environmental health. The objective of this study was to determine the N application rate to cool-season grass species that optimizes economic return without elevating herbage or soil NO 3 -N levels. Four N rates were applied in split applications to established stands of orchardgrass (Dactylis glomerata L.), smooth bromegrass (Bromas inermis Leyss.), tall fescue (Festuca arundinacea Schreb.), and timothy (Phleum pratense L.) near State College, PA, on a Murrill silt loam (fine-loamy, mixed, mesic Typic Hapludults) soil. Harvest treatments of three and four times per year were imposed on each Grass x N treatment. Economically optimum N rates (EONR) were 284, 368, and 299 kg N ha - 1 or 26, 32, and 29 kg N Mg - 1 of forage harvested for orchardgrass, tall fescue, and timothy, respectively. Smooth bromegrass did not reach an economic plateau at the highest (402 kg ha - 1 ) N rate. At EONR, NO 3 -N concentration exceeded 1000 mg kg in forage from early season harvests when four harvests per year were taken but not when three harvests per year were taken. Soil NO 3 -N concentration generally was not elevated above background levels when EONR was applied to orchardgrass or tall fescue. Our results, in conjunction with results from New York, indicate that the EONR for the cool-season grasses and harvest systems evaluated is 5 to 10 kg N Mg - 1 of dry forage greater than current recommendations in New York and Pennsylvania. However, continued research is needed in a wider range of climates and soil types using various N sources.
Wavelet‐based Heat Kernel Derivatives: Towards Informative Localized Shape Analysis

In this paper, we propose a new construction for the Mexican hat wavelets on shapes with applications to partial shape matching. Our approach takes its main inspiration from the well‐established methodology of diffusion wavelets. This novel construction allows us to rapidly compute a multi‐scale family of Mexican hat wavelet functions, by approximating the derivative of the heat kernel. We demonstrate that this leads to a family of functions that inherit many attractive properties of the heat kernel (e.g. local support, ability to recover isometries from a single point, efficient computation). Due to its natural ability to encode high‐frequency details on a shape, the proposed method reconstructs and transfers δ ‐functions more accurately than the Laplace‐Beltrami eigenfunction basis and other related bases. Finally, we apply our method to the challenging problems of partial and large‐scale shape matching. An extensive comparison to the state‐of‐the‐art shows that it is comparable in performance, while both simpler and much faster than competing approaches.
Holographic complexity for nonlinearly charged Lifshitz black holes

Using ‘complexity = action’ proposal we study the late time growth rate of holographic complexity for nonlinear charged Lifshitz black hole with a single horizon or two horizons. As a toy model, we consider two kinds of such black holes: nonlinear charged Lifshitz black hole and nonlinear logarithmic charged Lifshitz black hole. We find that for the black hole with two horizons, the action growth bound is satisfied. But for the black hole with a single horizon, whether the Lloyd bound is violated depends on the specific value of dimensionless coupling constants β 1, β 2, spacetime dimension D and dynamical exponent z.
TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP

While there has been substantial research using adversarial attacks to analyze NLP models, each attack is implemented in its own code repository. It remains challenging to develop NLP attacks and utilize them to improve model performance. This paper introduces TextAttack, a Python framework for adversarial attacks, data augmentation, and adversarial training in NLP. TextAttack builds attacks from four components: a goal function, a set of constraints, a transformation, and a search method. TextAttack’s modular design enables researchers to easily construct attacks from combinations of novel and existing components. TextAttack provides implementations of 16 adversarial attacks from the literature and supports a variety of models and datasets, including BERT and other transformers, and all GLUE tasks. TextAttack also includes data augmentation and adversarial training modules for using components of adversarial attacks to improve model accuracy and robustness.TextAttack is democratizing NLP: anyone can try data augmentation and adversarial training on any model or dataset, with just a few lines of code. Code and tutorials are available at https://github.com/QData/TextAttack.
Ants as biological control agents in agricultural cropping systems

Ants positively impact agricultural systems by rapidly consuming large numbers of pest insects, disturbing pests during feeding and oviposition, and increasing soil quality and nutrients. The ability of ants to control pest species has been recognized since the year 300 A.D. and farmers continue to conserve and promote ant populations in agricultural systems worldwide. Naturally occurring ant species in milpas, mango, citrus, coconut, cashews, and cotton control many pest insects. Through judicious insecticide application and changes in management practices such as tillage, and other manipulations of vegetation and crop structure, beneficial ant populations are conserved in a variety of agroecosystems. The first recorded example of biological control was the manipulation of ants throughout citrus orchards in Asia. Augmentation continues in citrus, and methods of ant introduction have been developed in Malaysian and Indonesian cocoa plantations, as well as to control sweet potato and banana weevils in Cuba. Ant species have been formally incorporated into other integrated pest management programs for cashew in Australia, cocoa in Papua New Guinea, and mango in Australia and Vietnam. With efforts to reduce chemical pesticide input in agricultural systems, research evaluating the ability of generalist ant species to control pest insects must continue.
DC-DistADMM: ADMM Algorithm for Constrained Optimization Over Directed Graphs

This article reports an algorithm for multiagent distributed optimization problems with a common decision variable, local linear equality, and inequality, constraints and set constraints with convergence rate guarantees. The algorithm accrues all the benefits of the alternating direction method of multipliers (ADMM) approach. It also overcomes the limitations of existing methods on convex optimization problems with linear inequality, equality, and set constraints by allowing directed communication topologies. Moreover, the algorithm can be synthesized distributively. The developed algorithm has: first, a <inline-formula><tex-math notation="LaTeX">$O(1/k) $</tex-math></inline-formula> rate of convergence, where <inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> is the iteration counter, when individual functions are convex but not-necessarily differentiable, and second, a geometric rate of convergence to any arbitrary small neighborhood of the optimal solution, when the objective functions are smooth and restricted strongly convex at the optimal solution. The efficacy of the algorithm is evaluated by a comparison with state-of-the-art constrained optimization algorithms in solving a constrained distributed <inline-formula><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula>-regularized logistic regression problem, and unconstrained optimization algorithms in solving a <inline-formula><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula>-regularized Huber loss minimization problem. Additionally, a comparison of the algorithm's performance with other algorithms in the literature that utilize multiple communication steps is provided.
Properties of the CGM and IGM: constraints on galaxy formation models from the Sunyaev-Zel'dovich effect

We present a comparison of the physical properties of the gas in the circumgalactic (CGM) and intergalactic (IGM) media at $z\sim0$ between observations and four cosmological hydrodynamical simulations: Illustris, TNG300 of the IllustrisTNG project, EAGLE, and one of the Magneticum simulations. For the observational data, we use the gas properties that are inferred from cross-correlating the Sunyaev-Zel'dovich effect (SZE) from the {\it Planck} CMB maps with the haloes and the large-scale structure reconstructed from Sloan Digital Sky Survey data. Both the observational and simulation results indicate that the integrated gas pressure in haloes deviates from the self-similar case, showing that feedback impacts haloes with $M_{500}\sim 10^{12-13}\,{\rm M_\odot}$. The simulations predict that more than half the baryons are displaced from haloes, while the gas fraction inferred from our observational data roughly equals the cosmic baryon fraction throughout the $M_{500}\sim 10^{12-14.5}\,{\rm M_\odot}$ halo mass range. All simulations tested here predict that the mean gas temperature in haloes is about the virial temperature, while that inferred from the SZE is up to one order of magnitude lower than that from the simulations (and also from X-ray observations). While a remarkable agreement is found for the average properties of the IGM between the observation and some simulations, we show that their dependence on the large-scale tidal field can break the degeneracy between models that show similar predictions otherwise. Finally, we show that the gas pressure and the electron density profiles from simulations are not well described by a generalized NFW (GNFW) profile. Instead, we present a new model with a mass-dependent shape that fits the profiles accurately.
A Survey on Vehicular Edge Computing: Architecture, Applications, Technical Issues, and Future Directions

A new networking paradigm, Vehicular Edge Computing (VEC), has been introduced in recent years to the vehicular network to augment its computing capacity. The ultimate challenge to fulfill the requirements of both communication and computation is increasingly prominent, with the advent of ever-growing modern vehicular applications. With the breakthrough of VEC, service providers directly host services in close proximity to smart vehicles for reducing latency and improving quality of service (QoS). This paper illustrates the VEC architecture, coupled with the concept of the smart vehicle, its services, communication, and applications. Moreover, we categorized all the technical issues in the VEC architecture and reviewed all the relevant and latest solutions. We also shed some light and pinpoint future research challenges. This article not only enables naive readers to get a better understanding of this latest research field but also gives new directions in the field of VEC to the other researchers.
Rapid, Noninvasive Diagnosis of Balamuthia mandrillaris Encephalitis by a Plasma-Based Next-Generation Sequencing Test

Abstract Granulomatous amoebic encephalitis (GAE) caused by Balamuthia mandrillaris is a rare subacute infection with exceptionally high mortality. Diagnosis is typically made by brain biopsy or at autopsy. Detection of Balamuthia mandrillaris cell-free DNA by next-generation sequencing of plasma enabled rapid, noninvasive diagnosis in a case of amoebic encephalitis.
Neurotrophins: New Players, Clinical Uses?

The elucidation within the past few years of a wide array of neurotrophic growth factors has been one of the important advances in the neurosciences. These factors are small proteins that exert powerful growth, differentiation, and tropic effects on specific neuron types via specific receptors and their signaling pathways. These characteristics have generated ex citement within the clinical fields of neurology and psychiatry because therapeutic oppor tunities exist in nearly all areas. Currently, the clinical trials are for neurodegenerative dis eases such as amyotrophic lateral sclerosis and Alzheimer's-type dementia. However, preclinical studies span across afflictions as diverse as epilepsy, drug addiction, and de pression. This Update briefly describes the general characteristics of the neurotrophic fac tors and discusses some of the potential clinical uses. The Neuroscientist 1:119-122,1995
Ecology and economics for pandemic prevention

Investments to prevent tropical deforestation and to limit wildlife trade will protect against future zoonosis outbreaks For a century, two new viruses per year have spilled from their natural hosts into humans (1). The MERS, SARS, and 2009 H1N1 epidemics, and the HIV and coronavirus disease 2019 (COVID-19) pandemics, testify to their damage. Zoonotic viruses infect people directly most often when they handle live primates, bats, and other wildlife (or their meat) or indirectly from farm animals such as chickens and pigs. The risks are higher than ever (2, 3) as increasingly intimate associations between humans and wildlife disease reservoirs accelerate the potential for viruses to spread globally. Here, we assess the cost of monitoring and preventing disease spillover driven by the unprecedented loss and fragmentation of tropical forests and by the burgeoning wildlife trade. Currently, we invest relatively little toward preventing deforestation and regulating wildlife trade, despite well-researched plans that demonstrate a high return on their investment in limiting zoonoses and conferring many other benefits. As public funding in response to COVID-19 continues to rise, our analysis suggests that the associated costs of these preventive efforts would be substantially less than the economic and mortality costs of responding to these pathogens once they have emerged.
Morphological and Histological Studies on the Epididymis and Deferent Duct of the Sunda Porcupine (Hystrix javanica)

Abstract. The Sunda porcupine (Hystrix javanica) is an endemic species of Indonesia. The population of this species has been decreased by hunting and habitat loss. Understanding of reproductive characteristics is essential for the appropriate management of their population. However, there is little knowledge about reproductive features of this species. The epididymis and deferent duct are important organs for maturation, transport, and storage of sperm. In this study, therefore, the epididymis and deferent duct of Sunda porcupines were examined histologically, histochemically, immunohistochemically, and electron-microscopically to understand their structures and functions. Four adult wild porcupines that inhabit Central Java, Indonesia, were captured in June and September and euthanized. Then, the epididymides and deferent ducts were removed. Principal cells were the main cell type found in the epididymis with stereocilia and apical blebs, but both of these structures were absent in the deferent duct. These observations suggest high secretion and absorption capability by the epididymal epithelium. In the epididymis and deferent duct, PAS-positive principal cells were shown, and the immunoreactivities for 3β-HSD were found in the epithelium of the deferent ducts. These reults suggest effects on sperm by glycoproteins and steroid metabolites.
Facultative brood parasitism by an American Robin (Turdus migratorius) in the nest of a Gray Catbird (Dumetella carolinensis)

ABSTRACT Avian brood parasites can be classified as either obligate or facultative. Obligate brood parasites, such as Brown-headed Cowbirds (Molothrus ater), must lay their eggs in the nests of other species because they exhibit no parental care. Although facultative brood parasitism, when species that would normally lay eggs in their own nests dump eggs in the nest of another individual, may occur frequently among conspecifics, facultative interspecific brood parasitism is relatively rare. Here I report on observations made during the breeding season of 2018 of an example of facultative brood parasitism by an American Robin (Turdus migratorius) in the nest of a Gray Catbird (Dumetella carolinensis). Two robin eggs were laid in the nest of the catbird and were successfully raised by the catbird to fledging age. Although the young of obligate brood parasitic cowbirds are rarely raised successfully by catbirds, this is the first documented example, of which I am aware, of a Gray Catbird successfully raising the young of a facultative brood parasite.