Miracle-dz/UniFAR-FTUs huggingface dataset:
GLOBAL ORIENTATIONAL ORDER IN MODEL POLAR CLUSTERS

Overall rotational anisotropy is found to be generic in compact clusters of model dipolar particles. This broken rotational symmetry, or ‘‘global’’ orientational order, is pronounced in zero temperature configurations. It arises from the tendency of dipolar particles to form head‐to‐tail chains which encircle the cluster, giving rise to a circulating pattern. In many cases, the zero temperature arrangement of dipolar particles is chiral. Expansion of the dipole density field in vector spherical harmonics provides order parameters to quantify broken orientational symmetry, and facilitates analysis of inversion and reflection symmetry. Finite temperature simulations of a 13‐particle cluster with Stockmayer (Lennard‐Jones+point dipole) interactions indicates that the global orientational order persists to higher temperatures, even above the point of translational melting. The 13‐particle Stockmayer cluster remains orientationally ordered up to the onset of frequent evaporation from the cluster. Ramifications.
Bioelectrochemical systems for nitrogen removal and recovery from wastewater

Removal of nitrogen compounds from wastewater is essential to prevent pollution of receiving water bodies (i.e. eutrophication). Conventional nitrogen removal technologies are energy intensive, representing one of the major costs in wastewater treatment plants. For that reason, innovations in nitrogen removal from wastewater focus on the reduction of energy use. Bioelectrochemical systems (BESs) have gained attention as an alternative to treat wastewater while recovering energy and/or chemicals. The combination of electrodes and microorganisms has led to several methods to remove or recover nitrogen from wastewater via oxidation reactions, reduction reactions and/or transport across an ion exchange membrane. In this study, we give an overview of nitrogen removal and recovery mechanisms in BESs based on state-of-the-art research. Moreover, we show an economic and energy analysis of ammonium recovery in BESs and compare it with existing nitrogen removal technologies. We present an estimation of the conditions needed to achieve maximum nitrogen recovery in both a microbial fuel cell (MFC) and a microbial electrolysis cell (MEC). This analysis allows for a better understanding of the limitations and key factors to take into account for the design and operation of MFCs and MECs. Finally, we address the main challenges to overcome in order to scale up and put the technology in practice. Overall, the revenues from removal and recovery of nitrogen, together with the production of electricity in an MFC or hydrogen in an MEC, make ammonium recovery in BESs a promising concept.
RECENT DEVELOPMENTS IN THE APPLICATION OF LIQUID METAL ION SOURCES TO SIMS

High-brightness liquid metal ion sources (LMIS) allow SIMS micr 4probe analysis with 50 nm spatial resolution at current densities > 1Atcm . Chemical imaging of matrix and trace elements on the submicron scale is now achieved using a digital image storage system. aliowing picture processing and direct comparison of SEM and SIMS images using colour overlays. While high-sensitivity quadrupole mass spectrometers have been developed for SIMS imaging. the ultimate in sensitivity requires magnetic or timeof-flight mass spectrometers.
Theoretical Study of Kinetics and Mechanism of Reactions of Hydroxylamine and Amineoxide Anion with Methyl Iodide in Gas and Aqueous Phases

The kinetics and mechanism of the reactions of hydroxylamine and aminoxide anion with methyl iodide were studied with ab initio calculations, Monte-Carlo and QM/MM simulations in gas and aqueous phases. Geometrical parameters and charge calculations show that these reactions proceed through the SN2 (bimolecular nucleophilic displacement) mechanism only. The solvent effects on these reactions were studied by inserting water molecules in reaction media, Onsager model, Monte-Carlo and QM/MM simulations. Activation parameters indicate the expected variation in activation energy and rate coefficient in aqueous phase in comparison to the gas phase. The shift of potential energy barrier through the reactants or products for the studied reactions in the gas phase is in the opposite direction in comparison to the aqueous phase.
Descortesía y comportamientos sexistas reproducidos por mujeres en la cultura rioplatense

El presente trabajo se propone analizar actividades de imagen descorteses surgidas de comportamientos verbales sexistas internalizados y recreados por las propias mujeres, comportamientos que concurren a modelar la identidad social femenina en la cultura rioplatense. Tales actividades de imagen descorteses se extraen de un corpus de discurso mediatico recogido en Internet. Esta investigacion se enmarca teorica y metodologicamente en la pragmatica sociocultural, en el analisis del discurso de descortesia del espanol rioplatense. Los resultados del analisis muestran que, por un lado, tales comportamientos verbales sexistas y descorteses asumidos como propios por parte de mujeres contribuyen a promover y a propagar la ideologia androcentrica del universo de creencias del grupo del que las mujeres forman parte; y, por el otro, aseguran la pervivencia de premisas culturales que representan estereotipos negativos de la imagen social femenina.
Larvicidal potentials of selected plants against Culex quinquefasciatus (Say, 1823) (Diptera: Culicidae) in Owerri Imo State, Nigeria

During the last decades lot of studies on natural plants as larvicides against mosquitoes has indicated positive results and can be used as alternatives against pesticides. The present study is focused on natural plants with insecticidal properties for control of Culex quinquefasciatus. Aqueous, methanol and Acetone were evaluated against the 4 th instar larvae of C. quinquefasciatus, an important filariasis vector. Phytochemical screening of the plants showed the presence of phyto compounds such as tannins, alkaloids, flavonoids, saponins, steroids, Quinones, Phenols and Glycosids. Different concentrations (10%-60%) of the extraction were used. Mortality of the larvae was observed within 24hrs of exposure. Results showed that higher extracts concentrations were greater in efficacy as compared to lower concentrations. It is concluded that all the 6 species of plants and parts used can be used for the prevention and control of C. quinquefasciatus mosquito due to there pesticide properties and bioactive chemicals and can be considered for further investigations.
Effects of selected amendments on soil properties and emergence of wheat seedlings

Crusting can have a prominent effect on seedling emergence. Crust formation at the soil surface is a common feature of many soils including the silty loam soil (Aquic Haplocalsids) from the Konya plain examined in this investigation. The effects of different soil amendments on modulus of rupture and aggregate stability in water were measured in a pot experiment in the laboratory. Seedling emergence of wheat (Triticum durum Desf.) and penetration resistance was investigated in a microplot experiment in the greenhouse. Portland cement, barnyard manure (dairy cattle), city waste compost (municipal refuse) and wheat straw were used in the pot experiment, and Portland cement and barnyard manure were investigated in the microplot experiment. Soil amendments were added to the soil samples at rates of 0, 2, 4 and 6% (wt/wt) and the samples including a control were incubated at about field capacity water content for up to 100 d in the laboratory. The moduli of rupture values and water stable aggregates were measur.
Characterization of Cu-CuTCNQ-M devices using scanning electron microscopy and scanning tunneling microscopy

These techniques are used to determine the morphology of CuTCNQ films made using solution phase and vapor phase spontaneous formation methods. Values of film thickness range from 0.1-20μm. All the films, irrespective of their method of preparation, display roughness on the order of their thickness. On the other hand, the morphology of these films varied significantly with preparation procedure.
Phase behavior of symmetric binary mixture with partially miscible components in slitlike pores: Density functional approach

We investigate adsorption of a model symmetric binary mixture, exhibiting demixing in a bulk phase, in slitlike pores by using a density functional approach. Our focus is on the evaluation of the first-order phase transitions between adsorbed phases and lines delimiting mixed and demixed adsorbed phases. The scenario for phase changes is sensitive to the pore width and to the energy of adsorption. Both these parameters can qualitatively change the phase behavior of the confined fluid. In particular, for relatively wide pores and for strong wall–fluid interactions, a demixing line can precede the first-order transition. Moreover, a competition between layering type behavior and demixing within particular layers also can lead to further complications of the phase diagram, reflected by the presence of consecutive branches, describing the equilibrium between different adsorbed phases.
Frame-Level Specaugment for Deep Convolutional Neural Networks in Hybrid ASR Systems

Inspired by SpecAugment — a data augmentation method for end-to-end ASR systems, we propose a frame-level SpecAugment method (f-SpecAugment) to improve the performance of deep convolutional neural networks (CNN) for hybrid HMM based ASR systems. Similar to the utterance level SpecAugment, f-SpecAugment performs three transformations: time warping, frequency masking, and time masking. Instead of applying the transformations at the utterance level, f-SpecAugment applies them to each convolution window independently during training. We demonstrate that f-SpecAugment is more effective than the utterance level SpecAugment for deep CNN based hybrid models. We evaluate the proposed f-SpecAugment on 50-layer Self-Normalizing Deep CNN (SNDCNN) acoustic models trained with up to 25000 hours of training data. We observe f-SpecAugment reduces WER by 0.5-4.5% relatively across different ASR tasks for four languages. As the benefits of augmentation techniques tend to diminish as training data size increases, the large scale training reported is important in understanding the effectiveness of f-SpecAugment. Our experiments demonstrate that even with 25k training data, f-SpecAugment is still effective. We also demonstrate that f-SpecAugment has benefits approximately equivalent to doubling the amount of training data for deep CNNs.
Linear Viscoelasticity of Disordered Polystyrene−Polyisoprene Block Copolymer Based Layered-Silicate Nanocomposites

The melt-state linear viscoelastic properties for a series of intercalated nanocomposites are examined. The nanocomposites are based on a short disordered polystyrene−polyisoprene diblock copolymer and varying amounts of dimethyldioctadecylammonium modified montmorillonite. The linear dynamic oscillatory moduli and the stress relaxation moduli are in quantitative agreement and suggest that at short times the relaxation of the nanocomposites is essentially unaffected by the presence of the layered-silicate. However, at long times (or equivalently low frequency), the hybrids exhibit dramatically altered viscoelastic behavior. Hybrids with silicate loadings in excess of 6.7 wt % exhibit pseudo-solidlike behavior, similar to that observed in previous studies of exfoliated end-tethered nanocomposites. On the basis of simple phenomenological arguments, the long time behavior is attributed to the presence of anisotropic stacks of silicate sheets randomly oriented and forming a percolated network structure that i.
Improved Swarm Engineering: Aligning Intuition and Analysis

When designing swarm-robotic systems, systematic comparison of swarm control algorithms is necessary to determine which can scale up to handle the target problem size and operating conditions. Qualitative predictions of performance based on algorithm descriptions are often incorrect, and can lead to costly design processes for swarm-robotic systems. We propose a set of quantitative measures for swarm scalability, emergence, flexibility, and robustness which enable swarm control algorithms analysis and comparison, swarm performance of a given control algorithm, collectively enabling quicker and more confident design decisions. We demonstrate the utility of our proposed measurements as modeling and design tools for real-world scenarios by analyzing two common problems, indoor warehouse object transport and search and rescue, and present experimental results obtained in simulation.
Access Control Mechanisms in Named Data Networks

Information-Centric Networking (ICN) has recently emerged as a prominent candidate for the Future Internet Architecture (FIA) that addresses existing issues with the host-centric communication model of the current TCP/IP-based Internet. Named Data Networking (NDN) is one of the most recent and active ICN architectures that provides a clean-slate approach for Internet communication. NDN provides intrinsic content security where security is directly provided to the content instead of communication channel. Among other security aspects, Access Control (AC) rules specify the privileges for the entities that can access the content. In TCP/IP-based AC systems, due to the client-server communication model, the servers control which client can access a particular content. In contrast, ICN-based networks use content names to drive communication and decouple the content from its original location. This phenomenon leads to the loss of control over the content, causing different challenges for the realization of efficient AC mechanisms. To date, considerable efforts have been made to develop various AC mechanisms in NDN. In this article, we provide a detailed and comprehensive survey of the AC mechanisms in NDN. We follow a holistic approach towards AC in NDN where we first summarize the ICN paradigm, describe the changes from channel-based security to content-based security, and highlight different cryptographic algorithms and security protocols in NDN. We then classify the existing AC mechanisms into two main categories: Encryption-based AC and Encryption-independent AC. Each category has different classes based on the working principle of AC (e.g., Attribute-based AC, Name-based AC, Identity-based AC). Finally, we present the lessons learned from the existing AC mechanisms and identify the challenges of NDN-based AC at large, highlighting future research directions for the community.
The First Law of Black Hole Mechanics

The first law of black hole mechanics has been the main motivation for investigating thermodynamic properties of black holes. The first version of this law was proved in \cite{Bardeen:1973gs} by considering perturbations of an asymptotically flat, stationary black hole spacetime to other stationary black hole spacetimes. This result was then extended to fully general perturbations, first in the context of Einstein-Maxwell theory in \cite{Sudarsky:1992ty},\cite{Wald:1993ki}, and then in the context of a general diffeomorphism invariant theory of gravity with an arbitrary number of matter fields in \cite{Wald:1993nt},\cite{Iyer:1994ys}. Here a review of these two generalizations of the first law is presented, with particular attention to outlining the necessary formalisms and calculations in an explicit and thorough way, understandable at a graduate level. The open problem of defining the entropy for a dynamical black hole that satisfies a form of the second law of black hole mechanics is briefly discussed.
Improving Clinical Document Understanding on COVID-19 Research with Spark NLP

Following the global COVID-19 pandemic, the number of scientific papers studying the virus has grown massively, leading to increased interest in automated literate review. We present a clinical text mining system that improves on previous efforts in three ways. First, it can recognize over 100 different entity types including social determinants of health, anatomy, risk factors, and adverse events in addition to other commonly used clinical and biomedical entities. Second, the text processing pipeline includes assertion status detection, to distinguish between clinical facts that are present, absent, conditional, or about someone other than the patient. Third, the deep learning models used are more accurate than previously available, leveraging an integrated pipeline of state-of-the-art pretrained named entity recognition models, and improving on the previous best performing benchmarks for assertion status detection. We illustrate extracting trends and insights, e.g. most frequent disorders and symptoms, and most common vital signs and EKG findings, from the COVID-19 Open Research Dataset (CORD-19). The system is built using the Spark NLP library which natively supports scaling to use distributed clusters, leveraging GPUs, configurable and reusable NLP pipelines, healthcare specific embeddings, and the ability to train models to support new entity types or human languages with no code changes.
Strong Error Estimates for a Space-Time Discretization of the Linear-Quadratic Control Problem with the Stochastic Heat Equation with Linear Noise

We propose a time-implicit, finite-element based space-time discretization of the necessary and sufficient optimality conditions for the stochastic linear-quadratic optimal control problem with the stochastic heat equation driven by linear noise of type $[X(t)+\sigma(t)]dW(t)$, and prove optimal convergence w.r. t. both, space and time discretization parameters. In particular, we employ the stochastic Riccati equation as a proper analytical tool to handle the linear noise, and thus extend the applicability of the earlier work [16], where the error analysis was restricted to additive noise.
Structural, Doped, Radiation Defects and Properties of Non-Stoichiometrical Solids

The paper includes experimental and theoretical data on spectral properties of oxide single crystals doped with ions of the iron group elements, as well as on the stability of ions oxidation state under irradiation. Experimental data resulting from the investigation of radiation-induced defects into pure and doped single crystals, such as sapphire (α-Al2O3) and garnets (Y3Al5O12, Gd3Ga2Sc3O12, Gd3Sc2Al3O12), are presented. The main conditions of creation of irradiation-induced color centers and point defects, including theoretical analysis, are considered too.
Structural Investigation of Water/Lecithin/Cyclohexane Microemulsions by FT-IR Spectroscopy

Abstract FT-IR spectra of water/lecithin/deuterated cyclohexane microemulsions as a function of water/lecithin molar ratio R ( R = [water]/[lecithin]) at various volume fractions ( O ) of the micellar phase have been recorded at 25°C. After elimination of the small spectral contributions due to deuterated cyclohexane and normalization, the shape of the C–H stretching band due to lecithin has been found dependent upon R and O whereas that of the O–H stretching band has been found dependent only upon R . The change in shape of the C–H band was interpreted in terms of a modification of the lecithin alkyl chain packing order. The analysis of the O–H band provides evidence that the hydroxylic groups of lecithin form strong hydrogen bonds whereas the added water is confined in bulk-like water domains.
Resource-Constrained Optimal Experimental Design.

The goal of this paper is to make Optimal Experimental Design (OED) computationally feasible for problems involving significant computational expense. We focus exclusively on the Mean Objective Cost of Uncertainty (MOCU), which is a specific methodology for OED, and we propose extensions to MOCU that leverage surrogates and adaptive sampling. We focus on reducing the computational expense associated with evaluating a large set of control policies across a large set of uncertain variables. We propose reducing the computational expense of MOCU by approximating intermediate calculations associated with each parameter/control pair with a surrogate. This surrogate is constructed from sparse sampling and (possibly) refined adaptively through a combination of sensitivity estimation and probabilistic knowledge gained directly from the experimental measurements prescribed from MOCU. We demonstrate our methods on example problems and compare performance relative to surrogate-approximated MOCU with no adaptive sampling and to full MOCU. We find evidence that adaptive sampling does improve performance, but the decision on whether to use surrogate-approximated MOCU versus full MOCU will depend on the relative expense of computation versus experimentation. If computation is more expensive than experimentation, then one should consider using our approach.
URoboSim - An Episodic Simulation Framework for Prospective Reasoning in Robotic Agents

Anticipating what might happen as a result of an action is an essential ability humans have in order to perform tasks effectively. On the other hand, robots capabilities in this regard are quite lacking. While machine learning is used to increase the ability of prospection it is still limiting for novel situations. A possibility to improve the prospection ability of robots is through simulation of imagined motions and the physical results of these actions. Therefore, we present URoboSim, a robot simulator that allows robots to perform tasks as mental simulation before performing this task in reality. We show the capabilities of URoboSim in form of mental simulations, generating data for machine learning and the usage as belief state for a real robot.
From Data Harvesting to Querying for Making Urban Territories Smart

This chapter provides a summarized, critical and analytical point of view of the data-centric solutions that are currently applied for addressing urban problems in cities. These solutions lead to the use of urban computing techniques to address their daily life issues. Data-centric solutions have become popular due to the emergence of data science. The chapter describes and discusses the type of urban challenges and how data science in urban computing can face them. Current solutions address a spectrum that goes from data harvesting techniques to decision making support. Finally, the chapter also puts in perspective families of strategies developed in the state of the art for addressing urban problems and exhibits guidelines that can lead to a methodological understanding of these strategies.