Miracle-dz/UniFAR-FTUs huggingface dataset:
Is there a wave excitation in the Thalamus

This paper proposes that the thalamus is the site of a wave excitation, whose function is to represent the locations of things around the animal. Neurons couple to the wave as transmitters and receivers. The wave acts as an analogue representation of local space. This has benefits over a purely neural representation of space. Several lines of evidence support this hypothesis; both theoretical, concerning efficient Bayesian inference in the brain, and empirical, concerning the neuro-anatomy of the thalamus. Across all species, the most basic function of the brain is to coordinate movements in space. To represent positions in space only by neural firing rates would be complex and inefficient. It is possible that that the brain represents 3D space in a direct and natural way, by a 3D wave
Effect of chronic ingestion of the cysteine proteinase inhibitor, E‐64, on Colorado potato beetle gut proteinases

Chronic ingestion of the highly active, specific cysteine proteinase inhibitor, E‐64, has a profound effect on Colorado potato beetle (CPB) larval growth, development and survival, as well as on adult fecundity. However, the number of insects surviving to the adult stage did not decrease below 26% with increasing E‐64 concentration above 1.5 μg E‐64 cm−2 leaf surface. The development time to the pupal stage was increased from 13 days, when larvae were reared on control leaves, to 21 days at a concentration of 1.5 μg E‐64 cm−2. The most significant effect of dietary E‐64 was on adult fecundity, with mated females reared on untreated leaves laying an average 62 ± 5.7 eggs daily in the first 10 days, and those maintained on 0.5 μg E‐64 cm−2, laying only 16 ± 2.4 eggs day−1. Females given 1 μg E‐64 cm−2 laid few if any eggs, but started producing egg masses as large as control insects about 5 days after being switched to control leaves. These effects on the insect life cycle were directly related to the degree of inhibition of cysteine proteinase activity in gut extracts. The general proteinase activity in control extracts was 6.5 ± 0.16 units min−1 mg gut−1, which decreased to 1.9 ± 0.16 in guts of insects reared on 1 μg E‐64 cm−2. The proportion of proteinase activity inhibitable by E‐64 decreased from 66% in control guts to 10‐15% in guts from larvae reared on 1 μg E‐64 cm−2. The aspartate proteinase inhibitor, pepstatin, decreased proteinase activity by 35% in control guts. There was no induction of pepstatin‐inhibitable proteinases in response to inhibition by E‐64, and no inhibition of gut enzyme activity by soybean trypsin inhibitor from larvae fed any of the E‐64 concentrations. This study demonstrates that proteinase levels must be significantly reduced to have a pronounced effect on larval growth and survival, while fecundity of mated females is affected by lower concentrations of inhibitor. It also suggests that the CPB may be a difficult pest to control using a more specific, plant‐derived cysteine proteinase inhibitor, such as oryzacystatin.
Laboratory analogy of astrophysical dynamos with intense lasers

The magnetic fields of most astrophysical objects are probably sustained by dynamos, which convert energy flow into a large scale magnetic field. Using three-dimensional particle-in-cell simulations, we show how a circularly polarized relativistic laser interacting with a plasma channel can start a scalable laboratory analogy of astrophysical dynamos. We observe plasma flowing towards the channel axis. These flows drive a plasma dynamo and amplify a seed magnetic field. The dynamo then persists on a picosecond time scale as long as the convection from the hot channel wall is maintained. For high laser powers, the dynamo can generate magnetic fields at gigagauss levels. The scheme might also be relevant for magnetized inertial confinement fusion.
A Soft Humanoid Hand with In-Finger Visual Perception

We present a novel underactued humanoid five finger soft hand, the KIT Finger-Vision Soft Hand, which is equipped with cameras in the fingertips and integrates a high performance embedded system for visual processing and control. We describe the actuation mechanism of the hand and the tendon-driven soft finger design with internally routed high-bandwidth flat-flex cables. For efficient on-board parallel processing of visual data from the cameras in each fingertip, we present a hybrid embedded architecture consisting of a field programmable logic array (FPGA) and a microcontroller that allows the realization of visual object segmentation based on convolutional neural networks. We evaluate the hand design by conducting durability experiments with one finger and quantify the grasp performance in terms of grasping force, speed and grasp success. The results show that the hand exhibits a grasp force of 31.8 ± 1.2 N and a mechanical durability of the finger of more than 15.000 closing cycles. Finally, we evaluate the accuracy of visual object segmentation during the different phases of the grasping process using five different objects. Hereby, an accuracy above 90 % can be achieved.
Variational Auto-encoder for Recommender Systems with Exploration-Exploitation

Variational auto-encoder (VAE) is an efficient non-linear latent factor model that has been widely applied in recommender systems (RS). However, a drawback of VAE for RS is their inability of exploration. A good RS is expected to recommend items that are known to enjoy and items that are novel to try. In this work, we introduce an exploitation-exploration motivated VAE (XploVAE) to collaborative filtering. To facilitate personalized recommendations, we construct user-specific subgraphs, which contain the first-order proximity capturing observed user-item interactions for exploitation and the higher-order proximity for exploration. We further develop a hierarchical latent space model to learn the population distribution of the user subgraphs, and learn the personalized item embedding. Empirical experiments prove the effectiveness of our proposed method on various real-world data sets.
Egocentric Object Manipulation Graphs

We introduce Egocentric Object Manipulation Graphs (Ego-OMG) - a novel representation for activity modeling and anticipation of near future actions integrating three components: 1) semantic temporal structure of activities, 2) short-term dynamics, and 3) representations for appearance. Semantic temporal structure is modeled through a graph, embedded through a Graph Convolutional Network, whose states model characteristics of and relations between hands and objects. These state representations derive from all three levels of abstraction, and span segments delimited by the making and breaking of hand-object contact. Short-term dynamics are modeled in two ways: A) through 3D convolutions, and B) through anticipating the spatiotemporal end points of hand trajectories, where hands come into contact with objects. Appearance is modeled through deep spatiotemporal features produced through existing methods. We note that in Ego-OMG it is simple to swap these appearance features, and thus Ego-OMG is complementary to most existing action anticipation methods. We evaluate Ego-OMG on the EPIC Kitchens Action Anticipation Challenge. The consistency of the egocentric perspective of EPIC Kitchens allows for the utilization of the hand-centric cues upon which Ego-OMG relies. We demonstrate state-of-the-art performance, outranking all other previous published methods by large margins and ranking first on the unseen test set and second on the seen test set of the EPIC Kitchens Action Anticipation Challenge. We attribute the success of Ego-OMG to the modeling of semantic structure captured over long timespans. We evaluate the design choices made through several ablation studies. Code will be released upon acceptance
Advection kinetics induced self-assembly of colloidal nanoflakes into microscale floral structures

The article explores the governing role of the internal soluto-thermal hydrodynamics and advective transport within sessile colloidal droplets on the self-assembly of nanostructures to form floral patterns. Water–acetone mixture and Bi2O3 nanoflakes based complex fluids are used as the experimental liquids. Micro-liter sessile droplets are allowed to vaporize and the dry-out patterns are examined using scanning electron microscopy. The presence of distributed self-assembled rose-like structures is observed and is postulated to be formed by the hydrodynamic interactions within the drying droplet. The population density, structure and shape of the floral structures are noted to be dependent on the binary fluid composition and nanomaterial concentration. Detailed microscopic particle image velocimetry and infrared thermography analysis is undertaken to qualitatively and quantitatively describe the solutal Marangoni advection within the evaporating droplets. It has been shown that the kinetics, regime and spatial distribution of the internal flows are dominantly responsible factors towards the advection influenced clustering, aggregation and self-assembly of the nanoflakes. In addition, the size of the nanostructures and the viscous character of the complex fluid are also noted to play dominant roles. The resulting interplay of hydrodynamic behavior, adhesion and cohesion forces during the droplet dry-out phase, and thermodynamic energy minimization leads to formation of such floral structures. The findings may have strong implications towards modulating micro-hydrodynamics induced self-assembly in complex fluids.
U-IMG2DSM: Unpaired Simulation of Digital Surface Models With Generative Adversarial Networks

High-resolution digital surface models (DSMs) provide valuable height information about the Earth’s surface, which can be successfully combined with other types of remotely sensed data in a wide range of applications. However, the acquisition of DSMs with high spatial resolution is extremely time-consuming and expensive with their estimation from a single optical image being an ill-possed problem. To overcome these limitations, this letter presents a new unpaired approach to obtain DSMs from optical images using deep learning techniques. Specifically, our new deep neural model is based on variational autoencoders (VAEs) and generative adversarial networks (GANs) to perform image-to-image translation, obtaining DSMs from optical images. Our newly proposed method has been tested in terms of photographic interpretation, reconstruction error, and classification accuracy using three well-known remotely sensed data sets with very high spatial resolution (obtained over Potsdam, Vaihingen, and Stockholm). Our experimental results demonstrate that the proposed approach obtains satisfactory reconstruction rates that allow enhancing the classification results for these images. The source code of our method is available from: https://github.com/mhaut/UIMG2DSM.
Emergent pattern formation of active magnetic suspensions in an external field

We study collective self-organization of weakly magnetic active suspensions in a uniform external field by analyzing a mesoscopic continuum model that we have recently developed. Our model is based on a Smoluchowski equation for a particle probability density function in an alignment field coupled to a mean-field description of the flow arising from the activity and the alignment torque. Performing linear stability analysis of the Smoluchowski equation and the resulting orientational moment equations combined with non-linear 3D simulations, we provide a comprehensive picture of instability patterns as a function of strengths of activity and magnetic field. For sufficiently high activity and moderate magnetic field strengths, the competition between the activity-induced flow and external magnetic torque renders a homogeneous polar steady state unstable. As a result, four distinct dynamical patterns of collective motion emerge. The instability patterns for pushers include traveling sheets governed by bend-twist instabilities and dynamical aggregates. For pullers, finite-sized and system spanning pillar-like concentrated regions predominated by splay deformations emerge which migrate in the field direction. Notably, at very strong magnetic fields, we observe a reentrant hydrodynamic stability of the polar steady state.
Analytic Solutions of the Rotating and Stratified Hydrodynamical Equations

In this article we investigate the two-dimensional incompressible rotating and stratified, just rotating, just stratified Euler equations with each other and with the normal Euler equations with the self-similar Ansatz. There are analytic solutions available for all four models, for density, pressure and velocity fields, some of them are compound power-law dependent functions. In general the solutions have a rich mathematical structure. Some solutions show unphysical explosive properties others, however are physically acceptable and have finite numerical values with power law decays. For a better transparency we present some figures for the most complicated velocity and pressure fields.
Quantitative PCR Revealed a Minority of ITS Copies to Be Functional in Mammillaria (Cactaceae)

The increasing number of pseudogenic internal transcribed spacer (ITS) regions (ITS1, 5.8S rDNA, ITS2) reported for plant taxa raises questions—for example, concerning the proportion of functional copies. Our application of quantitative PCR (qPCR) with genomic DNA under stringent conditions revealed that <3% of the copies of the ITS region were putatively functional in the genomic PCR pool in Mammillaria. The selective amplification of functional copies of the ITS region was possible through the utilization of conserved angiosperm motifs (ITS1 motif and 5.8S motif) as primer annealing sites. Our study displays that it is possible to quantify the proportion of functional copies of repetitive DNA regions through their selective amplification by qPCR.
Identification of basidiomycete fungi in Indonesian hardwood plantations by DNA barcoding

An investigation of root rot in Acacia mangium plantations in Indonesia generated over 1000 fungal isolates from field surveys at six locations. The majority of isolates were identified as Ganoderma philippii or Ganoderma mastoporum by species-specific PCR, but this still left 274 isolates to be identified. As barcoding initiatives for fungi are still in the early stages, to assist identification of these isolates in this way we developed a database of sequences based on identified sporocarps and also searched public DNA sequence databases for sequences with high similarity. The database of sequences from sporocarp collections is more limited than public DNA databases. This resulted in more reliance on public DNA databases for a high proportion of taxa. Several pathogenic species were identified, with Phellinus noxius occurring at several locations and on both A. mangium and Eucalyptus pellita . Ganoderma steyaertanum was isolated from A. mangium roots and Rigidoporus microporus from E. pellita roots, each at a single location only. Potential pitfalls of using public DNA databases for fungal identification are discussed and methods to avoid these and increase confidence in the identification are presented.
Description of Meiosis in Female and Male Pacific White Shrimp Litopenaeus vannamei (Decapoda: Penaeidae)

Abstract The first meiotic prophase was analyzed in both genders of Pacific white shrimp Litopenaeus vannamei. Progression through meiosis, from the formation of the synaptonemal complex to diplotene is described during molting stages. Most of the meiotic cells in both genders were observed at pachytene, recognized by complete synapsis of bivalents. In both genders, the zygotene, pachytene, and diplotene stages occurred at inter-molt, pre-molt, and post-molt stages in all individuals, which suggests that there is no relationship between molting and the first meiotic prophase. Sperm counts from the vas deferens and spermatophores support a continuous production of male gametes. The nature of the synaptonemal complex in gonad cells shows that each pair of homologous chromosomes synapses end to end, revealing a high chromatin density and a complex tangled arrangement in the nucleus. Both genders have 44 bivalents, of which around 40 have an o-ring configuration, and the rest have a v-shape, meaning that most bivalents present chiasmata at both ends, each representing two crossing-over events per bivalent per meiosis.
Distribution of saltmarsh plant communities associated with environmental factors along a latitudinal gradient on the south‐west Atlantic coast

Aim To produce an inventory of south‐west Atlantic saltmarshes (from latitude 31°48′ S to 43°20′ S) using remotely sensed images and field sampling; to quantify their total area; to describe the biogeographical variation of the main habitats characterized by dominant vascular plants, in relation to major environmental factors; to test the hypothesis of predominance of the reversal pattern in plant distribution (sedges and grasses dominate the lower, regularly inundated zones, while the upper zones are occupied by more halophytic species) previously described; and to compare these south‐west Atlantic saltmarshes with others world‐wide.
Analyses of Framework for Enhanced RFID Security and Privacy

Radio Frequency IDentification (RFID) is a method of remotely storing and retrieving data using small and inexpensive devices called RFID tags. In this paper we propose a proxy agent framework that uses a personal device for privacy enforcement and increased protection against eavesdropping, impersonation and cloning attacks. Using the proxy model a user decides when and where information carried in a tag will be released. In particular, the user can put tags under her/his control, authenticated requests, release tags, transfer them to new owners
Modelling Sustainable Competitive Advantage in Services Organisations.docx

For organisations to attain and/or maintain a sustainable competitive advantage they require a competitive orientated management system. The system should address key concepts such as leadership, personnel and development. However, the system also has to fully address the needs of stakeholders. Twenty-five different management function features are correlated with corporate profitability and stakeholder satisfaction. The study used Canonical correlation methods to correlate simultaneously the management function features to the assessment of competitive advantage measures. Through a survey of data collected from 39 employees and 5 managers from the Russian Service Industry, this study empirically refines and validates 5 constructs for management functions. The constructs refined in this study are compared with other major quality measurement instruments. The study reports on the operational framework of Management Functional Assessment Model (MFAM), which can be used to examine the levels of critical factors relating to competitive advantage. The findings indicate that the MFAM is both reliable and valid. Qualitative data was collected based on the following five management function constructs, namely, Forecasting Planning, Organising, Motivation, Control and Co-ordination. Based on a fuzzy scoring system, Construction organisations are able to rate the advancement of identified and validated Management Maturity. The result of the assessment, is a classification of the organisations into five different levels of management maturity in terms of achieving competitive advantage, ranging from Unaware to Achiever, and also identifies the strengths and weaknesses of their quality initiatives. The paper further explores the model’s constituent parts and relates them to the process of gathering data on organisational requirements focussed upon attaining/maintaining a competitive advantage.
Automatic disﬂuency detection in a dialogue system

Disﬂuency detection is the task of recognizing structural metadata in spoken utterances. It has been the topic of several studies in computational linguistics and psycholinguistics. This paper motivates the need for automatic disﬂuency detection in a dialogue system and delineates some of the features that characterize a disﬂuent utterance.
Asynchronous Decision-Making Dynamics Under Imitation in Heterogeneous Populations

We study a finite well-mixed heterogeneous population of individuals choosing between the two strategies cooperation and defection, and earning based on their payoff matrices that can be unique to each individual. At each time step, an arbitrary individual becomes active to update her decision by imitating the highest earner in the population. We take the distribution of the cooperators over the payoff matrices as the state of the dynamics. We show that in the long run, the dynamics almost surely reach either an equilibrium state or a non-singleton minimal positively invariant set, a fluctuation set. In addition to finding all equilibria and studying their stability, we characterize the fluctuation sets for the first time, and provide necessary and sufficient conditions for their existence. Our results theoretically explain earlier reported simulation results, shed new lights on the boundedly rational nature of imitation behaviors, and pave the way for future research on controlling such populations.
Biometric Quality: Review and Application to Face Recognition with FaceQnet

"The output of a computerised system can only be as accurate as the information entered into it. " This rather trivial statement is the basis behind one of the driving concepts in biometric recognition: biometric quality. Quality is nowadays widely regarded as the number one factor responsible for the good or bad performance of automated biometric systems. It refers to the ability of a biometric sample to be used for recognition purposes and produce consistent, accurate, and reliable results. Such a subjective term is objectively estimated by the so-called biometric quality metrics. These algorithms play nowadays a pivotal role in the correct functioning of systems, providing feedback to the users and working as invaluable audit tools. In spite of their unanimously accepted relevance, some of the most used and deployed biometric characteristics are lacking behind in the development of these methods. This is the case of face recognition. After a gentle introduction to the general topic of biometric quality and a review of past efforts in face quality metrics, in the present work, we address the need for better face quality metrics by developing FaceQnet. FaceQnet is a novel opensource face quality assessment tool, inspired and powered by deep learning technology, which assigns a scalar quality measure to facial images, as prediction of their recognition accuracy. Two versions of FaceQnet have been thoroughly evaluated both in this work and also independently by NIST, showing the soundness of the approach and its competitiveness with respect to current state-of-the-art metrics. Even though our work is presented here particularly in the framework of face biometrics, the proposed methodology for building a fully automated quality metric can be very useful and easily adapted to other artificial intelligence tasks.
Interaction Between Beams and Vacuum System Walls.

In modern high-intensity accelerators, the circulating beam interacts in many ways with the vacuum beam pipe, causing a variety of different phenomena. Most of them have been discussed at length in other contributions to this CAS report. I concentrate here on the effects associated with the presence of electrons in the accelerator beam pipes. Low-energy electrons in accelerators are known to interact with the circulating beam, giving raise to the formation of a so-called e$^-$ cloud. e$^-$ cloud effects can be detrimental to beam quality and stability, especially for positively charged beams. I will first describe the origin and the basic features causing e$^-$ cloud formation in accelerators, which depend not only on the beam properties but mainly on the vacuum vessel surface properties. Such material properties and the way one can study them will be here briefly presented. Finally, some of the e$^-$ cloud mitigation strategies adopted and proposed so far will be described and discussed.