Miracle-dz/UniFAR-FTUs huggingface dataset:
Intergenerational effects from spatial and genetic environment predict early-life social network structure

Early independence is a crucial stage in the ontogeny of social environments, but it is often challenging to study in the wild. Genetics may structure groups if young animals associate with familiar kin, but association opportunities also develop as a by-product of environmental processes such as spatial resource distribution. The contribution of these alternate factors in initial opportunities for bonding outside direct relatives is difficult to pick apart, despite its importance in shaping later life. However, species where genetics and spatial structure are less closely coupled (for example, via extra-pair mating) provide a natural opportunity to disentangle these effects. We addressed this gap by investigating the contribution of relatedness versus spatiotemporal synchrony (natal nest-box location and fledge timing) to early-life social structure in newly-independent young hihi (Notiomystis cincta). We also investigated the contribution of inbreeding in both juveniles and their parents, to individual-level sociality, as this genetic factor has had limited focus in studies of social structure. Using a long-term genetic pedigree, detailed breeding records, and social network data collected across three cohorts, we found that juvenile social associations were predicted by natal nest-box location, irrespective of relatedness between juveniles. Therefore, the physical environment can create initial opportunities for associations to develop once young animals disperse from natal sites. Furthermore, juvenile sociability was predicted by their father’s (but not mother’s) inbreeding, highlighting how genetics may have indirect and intergenerational effects on social behaviour. Overall, social structure in wild animals can emerge early in life if the natal environment determines association opportunities. These patterns may even be pre-determined across generations if breeding and settlement decisions made by parents affect the physical and social environments experienced by their offspring. Ultimately, our study highlights how influences on early life social structure may have important consequences for population dynamics and evolutionary potential.
Modified Affine Arithmetic-Based Power Flow Analysis with Uncertainty

Abstract Power flow studies are very important and are essential for fault analysis and stability analysis. Conventional Newton–Raphson-based power flow analysis is for fixed loads and generations. However, load and generation powers are uncertain due to factors like forecasting error, sudden outages, etc. Monte Carlo was widely used for power flow analysis with uncertainty. Due to excessive computational time involved in Monte Carlo, affine arithmetic-based power flow analysis was introduced. In the present work, a modified affine arithmetic-based power flow analysis is proposed. The proposed method needs less computational memory and gives tighter bounds on voltage magnitudes and angles of the system buses for a given uncertainty range of load and generation powers as compared to existing affine arithmetic-based power flow analysis. The proposed method is implemented on IEEE 30 and IEEE 118 bus systems and detailed simulation results are presented. The results are compared with Monte Carlo simulations as well as existing affine arithmetic-based power flow analysis. The results show that the proposed modified affine arithmetic-based power flow analysis yields more accurate solution intervals for voltage magnitude, voltage angles, real, and reactive power flows as compared to existing affine arithmetic-based power flow analysis.
Increasing Resolution of X-ray Imaging at High Acceleration Voltages

Driven by needs from scientific research, healthcare and industrial manufacturing, X-ray microscopy has been successfully transferred from synchrotrons to the laboratory and the spatial resolution has been pushed to sub-micrometer. One way to further improve the resolution is to use an X-ray source with a very small focal spot. At Excillum, based on advanced electron beam and target technologies, a state-ofart nanofocus x-ray tube has been developed which enables an isotropic, resolution of 150 nm linespacing all the way up to 160 kV of acceleration voltage.
Energy recovery and efficiency improvement for an activated sludge, agro-food WWTP upgrade

Wastewater treatment's primary purpose is to protect surface water quality, aquatic life, beneficial and recreational uses of waterways, and primarily comply with local water emission standards. Lately, additional requirements were added for these facilities, concerning minimization of a series of sidestream environmental impacts (i.e., odours, generated waste by-products, etc.), air emissions, including CO2, methane and nitrogen greenhouse gases (GHGs), and mitigation of various other likely impacts resulting from energy and chemical use in treatment processes. This paper describes a case study in Northern Europe, where critical analysis of an industrial wastewater treatment plant's present conditions, during an evaluation of upgrade possibilities to improve regulatory compliance, led to a sustainable intervention proposal. According to the formulated proposal, process improvement, energy recovery, and overall savings and GHG emissions reduction could be simultaneously achieved with a series of relatively simple interventions.
Physics-Based Simulation of Canine Gait

For most animals, locomotion is essential for survival, and it is advantageous to do this efficiently and with minimal neural control. Research has shown that efficient walking is possible without control, resulting purely from the mechanical design of the walker. It is understood that in running gaits, elasticity of muscles and tendons plays a role in preservation of energy. We first describe a rigid body physics engine that is designed specifically for simulating skeletal locomotion. This engine is then used to reproduce canine locomotion in two separate approaches. The first approach is to reproduce the gait of a real dog, as recorded using motion capture. Control is based on local quadratic minimization, and various techniques are used for stability, balance and steering. The second approach is to simulate efficient hoppers, including a two legged alternating hopper that is based on the anatomy of a dog. This hopper has minimal energy loss during ground collisions, and is controlled by changing muscle contractions when they are slack.
Using 3D Reconstruction Technique Along with Monte Carlo Modelling for Quantitative Characterizations of Fracture Surface of Monel Alloy

Quantitative microanalysis of rough surfaces is difficult in the scanning electron microscope. Although X-Ray microanalysis can be a useful tool for preliminary characterization, it is not quantitative because the complicated geometry of the rough surface introduces problems that are not present in the current models of quantitative microanalysis of a flat sample. The problem with the quantitative microanalysis of rough surfaces is that electrons can be scattered from all sides due to different slopes on the surface, so the generated x-rays depend on the roughness. Moreover, the orientation of slopes makes it difficult to correctly consider the path of characteristic x-rays between their generation locations and the surface [1, 2] making difficult to compute an absorption correction. Therefore, the geometry of the rough surface impacts the measured x-ray intensities and thereby the quantitative analysis of the sample. We propose to measure the geometrical information of the rough surface in the electron microscope and to compute X-Ray detection from the measured rough surface with Monte Carlo simulation to overcome this problem. In this work, we present preliminary results using a fracture surface of a Monel alloy (69%Ni-29%Cu-1%Fe-1%Mn, C, and Si). The 3D reconstruction of the rough surface was obtained using backscattered electron (BSE) images via the 4-Quadrant backscatter detector [3]. The existing Monte Carlo software MC X-ray [4] was incorporated into the image processing software Dragonfly developed by Object Research Systems (ORS) Inc [5]. The incorporation of the MC X-ray in Dragonfly allows users to do Monte Carlo simulation for any complicated geometry. Figure 1 shows SE, BSE images and EDS map of Ni Kα and Cu Kα of the fracture surface (Monel alloy) acquired with the Hitachi SU-3500 Electron Microscope equipped with an Oxford X-MAX
MRI Image Segmentation Using Conditional Spatial FCM Based on Kernel-Induced Distance Measure

Fuzzy C-means (FCM) clustering is the widest spread clustering approach for medical image segmentation because of its robust characteristics for data classification. But, it does not fully utilize the spatial information and is therefore very sensitive to noise and intensity inhomogeneity in magnetic resonance imaging (MRI). In this paper, we propose a conditional spatial kernel fuzzy C-means (CSKFCM) clustering algorithm to overcome the mentioned problem. The approach consists of two successive stages. First stage is achieved through the incorporation of local spatial interaction among adjacent pixels in the fuzzy membership function imposed by an auxiliary variable associated with each pixel. The variable describes the involvement level of each pixel for construction of membership functions and different clusters. Then, we adapted a kernel-induced distance to replace the original Euclidean distance in the FCM, which is shown to be more robust than FCM. The problem of sensitivity to noise and intensity inhomogeneity in MRI data is effectively reduced by incorporating a kernel-induced distance metric and local spatial information into a weighted membership function. The experimental results show that the proposed algorithm has advantages in accuracy and robustness against noise in comparison with the FCM, SFCM and CSFCM methods on MRI brain images.
Automatic 3D Reconstruction by Deep Learning Neural Networks Using Images Acquired via 4D-STEM Stereo Imaging

The stereo-pair approach for revealing the 3D distribution of dislocation structures from the transmission electron micrographs proved to be an effective alternative approach compared to laborious electron tomography [1, 2]. Further improvements occurred in the field of stereo 3D reconstruction with the development of a tilt-less imaging technique where a stereo-pair of images can be acquired in a single sample tilt using a convergent probe in scanning TEM mode (STEM) [3]. This technique brings many advantages such as the elimination of sample movement between two images and opens the avenue to dynamic imaging [4]. However, existing algorithms for post-processing and following 3D reconstruction were still slow and required human intervention. Therefore, we developed a methodology based on tilt-less 3D imaging [3] combined with deep learning convolutional neural networks (CNN) to automatically reconstruct the dislocations network in the 3D volume of a sample. Our approach allows us to automatically detect the dislocation structures and match them on both views without any prior assumptions about their 3D shape [5]. By applying tilt-less 3D imaging [3] on a fast pixelated STEM detector [6] and using our algorithm, we demonstrate the 3D reconstruction of dislocations
High Angle Liquid Cell TEM Tomography for In Situ Observation and 3D Reconstruction in Liquid

Liquid-Cell (LC) electron microscopy (EM) is a rapidly emerging field in EM [1]. While 2-D LC observations are very common for inorganic materials and biological systems, studies of molecular moieties in 3-D in the liquid environment are scarce [2, 3] mainly due to very limited available tilt range of the current LC holders (e.g
ULTRA-RELATIVISTIC, NEUTRINO-DRIVEN FLOWS IN GAMMA-RAY BURSTS: A DOUBLE TRANSONIC FLOW SOLUTION IN A SCHWARZSCHILD SPACETIME

The structure of a hydrodynamic, double transonic flow driven by neutrino annihilation in the polar region of a Schwarzschild black hole is computed for different energy deposition profiles. The requirement that both the inflow into the black hole and the outflow to infinity pass smoothly through their sonic points fixes the stagnation radius and stagnation pressure. The asymptotic power of the outflow is shown to be the integral of the energy deposition rate above the stagnation radius. The outflow production efficiency depends on the energy deposition profile and is generally higher for shallower profiles. Using recent calculations of the neutrino annihilation rate, we estimate that over 50% of the total energy deposited above the horizon can emerge in the form of a relativistic outflow at infinity. The continuous creation of plasma during the expansion of the outflow leads to generation of a large specific entropy. This has important implications for the prompt photospheric emission in gamma-ray bursts.
Calculation of Leakage in Water Supply Network Based on Blind Source Separation Theory

The economic and environmental losses due to serious leakage in the urban water supply network have increased the effort to control the water leakage. However, current methods for leakage estimation are inaccurate leading to the development of ineffective leakage controls. Therefore, this study proposes a method based on the blind source separation theory (BSS) to calculate the leakage of water supply network. The method uses fast independent component analysis (FastICA) algorithm to separate flow signal of laboratory and practical measuring area, adopts trend similarity to solve the uncertainty of separation sequence to get hourly change curve of user usage and physical leakage, and embeds the leakage model into amplitude optimization model to solve amplitude uncertainty to obtain physical leakage value. The study found that the estimation of leakage level using the blind source separation is reasonably accurate and facilitates the identification of the subsequent reduction in water leakage. This can provide scientific evidence for leakage reduction and the investment of pressure relief devices in the next stage.
Tactile sensing, perception and shape interpretation (cones)

Dextrous robot hands require intelligent control systems to manipulate unknown objects reliably in a complex environment. Tactile sensing and perception are needed to provide information on contact forces and local shape properties to ensure robust manipulation of objects. This thesis considers aspects of (1) tactile sensing from strain measurements in an elastic medium, (2) estimation of contact force and local shape, and (3) global object inferences from local geometric information at multiple fingers. A cylindrical tactile sensor using capacitive strain measurement techniques has been developed. Orthogonal copper strips separated by a rubber dielectric form an 8 by 12 array of capacitors. Pressure on the sensor surface changes the capacitor plate separation; a simple elastic model predicts this sensor behavior well, and is in agreement with extensive experimental measurements. This model and experimental results are used to examine the relations between sensor depth and sensor spacing, and limits to sensitivity, localization, and aliasing. We consider an unknown second-order surface indenting the finger. Principal curvatures, normal force and location are determined from a 4 by 4 window of strain measurements. Sensor strains are predicted by convolving the spatial impulse response of the rubber skin with the assumed surface pressure distribution derived from a Hertz contact model. Gradient search finds the parameters of the convex second-order shape and the force that best fit the sensor data. Experimental results for cylinders show radius estimation within 10%, orientation estimates within 2.5 degrees, and sub-tactel localization to within 3% of the element spacing. We can infer global properties of an unknown grasped object from local geometric properties, on multiple surface patches in contact. The location and orientation of a particular class of generalized cylinders, i.e. true cones, can be found from three ideal features, such as certain combinations of two edges and a face, or two faces and an edge. A hand control method is proposed that would use this tactile information to manipulate unknown objects.
A Convex Constraint for Directly Designing a Low-order Controller in Polynomial Approach

A convex constraint on controller parameters is proposed in order to decrease the controller order in any optimization-based controller design method in polynomial approach for LTI-SISO polytopic systems. It employs rank-deficiency constraint on the controller Sylvester resultant matrix, which is not convex itself. Therefore, an improved convex approximation of the rank deficiency constraint is used that can be represented via LMIs. The effectiveness of the proposed method is shown by appending it to an existing controller design method for polytopic systems in polynomial approach.
An Iconic Logic of Metaphors

Three theses are defended: (i) that metaphors create non-literal meaning; (ii) that metaphoric meaning is a matter of iconic logic; and (iii) that semantics of metaphors requires modal interpretation. The logic of metaphors takes similarity considerations to be central to iconicity. Similarity is a species of iconicity in the sense of Charles Peirce’s theory of diagrammatic signs. Consequence is a refutation of (i) meaning holism, (ii) the language of thought hypothesis, and (iii) psychologism about metaphoric meaning.
Approaches for High Resolution Cryo-Electron Tomography of Biological Specimens

Electron tomography is a powerful tool for elucidating the three-dimensional architecture of large biological complexes and subcellular organelles. Use of intermediate voltage electron microscopes extended the technique by providing the means to examine very large and non-symmetrical subcellular organelles, at resolutions beyond what would be possible using light microscopy. Recent studies using electron tomography on a variety cellular organelles and assemblies such as centrosomes (Moritz et al.,1995a,b), kinetochores (McEwen, 1993) and chromatin (Woodcock, 1994), have clearly demonstrated the power of this method for obtaining 3D structural information on non-symmetric cell components. When combined with biochemical and molecular observations, these 3D reconstructions have provided significant new insights into biological function. Although the information that tomography provides is unique, its use as a general tool in the biological community has been limited due to the complexities involved in data collection and processing. We are simultaneously trying to make this approach accessible through automation as well as trying to extend the resolution and accuracy of the reconstructions. Significant, has been the use of low-dose cryo-electron microscopic automated data collection methods.
On-Line Aberration Measurement and Correction in STEM

Aberration correction in electron microscopy is a subject with a 60 year history dating back to the fundamental work of Scherzer. There have been several partial successes, such as Deltrap's spherical aberration (Cs) corrector which nulled Cs over 30 years ago. However, the practical goal of attaining better resolution than the best uncorrected microscope operating at the same voltage remains to be fulfilled. Combining well-known electron-optical principles with stable electronics, versatile computer control, and software able to diagnose and correct aberrations on-line is at last bringing this goal within reach. We are building a quadrupole-octupole Cs corrector with automated aberration diagnosis for a VG HB5 dedicated scanning transmission electron microscope (STEM). A STEM with no spherical aberration will produce a smaller probe size with a given beam current than an uncorrected STEM, and a larger beam current in a given size probe.
On the hormonal inhibition of moulting in decapod crustacea

Recently I have reported experiments which have led me to throw doubt on the universal applicability of the theory of the production of a moult-inhibiting hormone by the eyestalks of the decapod Crustacea (Carlisle, 1953). I suggested that the eyestalk moult-inhibiting hormone might be associated with the existence of a definite moulting season. In animals which possessed such a moulting season moultingwould then be inhibited outside this season, but within the season there might well be no such inhibition. The experiments reported here support a modified form of this hypothesis.
Sheaves and Cauchy-complete categories

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Image Reconstruction from the Oversampled Diffraction Pattern

In recording the intensity of the diffraction pattern from an arbitrary object, the phase is lost. This gives rise to the “phase problem”in reconstructing the object in crystallography, where the pattern is sampled at the Bragg peaks. It was shown by Bates and by Hayes that sampling at twice crystallographic density (2x oversampling) in each dimension is sufficient in principle to obtain a full reconstruction of the object. It was pointed out by Sayre in 1991 that the diffraction pattern of a non-crystalline object is continuous, therefore the pattern may be sampled on a finer scale, providing the additional information for the image reconstruction. The loss of phase corresponds to a loss of half the information. It seems therefore that 2x oversampling in each dimension (8x in three dimension) may be unnecessary. We find that oversampling 1.67x in each dimension is sufficient to obtain a reconstruction, even in the presence of noise. However our algorithm fails when we reduce the oversampling factor to 1.58x.
Evaluation of systematic reviews of treatment or prevention interventions

In a previous article in this series we explained how the critical appraisal of research is an essential step in evidence-based health care because most published research is too poor in quality to be applied to clinical practice.1 Critical appraisal is made easier through the use of quality checklists that can help you to appraise research studies systematically and efficiently. The 3 basic appraisal questions are the same whether the clinical question is about treatment, diagnosis, prognosis, or causation: The first 2 articles in the EBN users' guide series focused on critical appraisal of primary studies of treatment or prevention.1,2 This guide will deal with critical appraisal of systematic reviews, beginning with a clinical scenario and applying the appraisal questions to the review by Glazener and Evans on the effectiveness of alarm interventions for nocturnal enuresis in children.4 ### How to critically appraise review articles Are the results of this systematic review valid? What were the results? Will the results help me in caring for my patients?
An Embedded PID Temperature Control Scheme with Application in a Medical Microwave Radiometer

Microwave radiometers are instruments for resolving blackbody radiation of heated matter above absolute zero, with many applications including breast cancer diagnosis. In this work a prototype microwave radiometer including a controllable noise reference generator was designed. The design of this noise source is based on the NC303 noise diode that delivers symmetrical white Gaussian noise and flat output power versus frequency (10MHz – 10GHz). An embedded PID control scheme is responsible for temperature stabilization of this sub-unit. The PID controller is designed to cope with disturbance rejection and set-point tracking problems. The first step in PID tuning involved extraction of the system’s open loop transfer function. Then the internal model control (IMC) method was used for tuning the controller and the resulting control scheme was successfully applied to the real system.