Miracle-dz/UniFAR-FTUs huggingface dataset:
Tracing the simulated high-redshift circum-galactic medium with Lyman α emission

With the Multi Unit Spectroscopic Explorer (MUSE), it is now possible to detect spatially extended Lyman alpha emission from individual faint (M_UV ~ -18) galaxies at redshifts, 3 < z < 6, tracing gas out to circum-galactic scales comparable to the dark matter halo virial radius. To explore the implications of such observations, we present a cosmological radiation hydrodynamics simulation of a single galaxy, chosen to be typical of the Lyman alpha-emitting galaxies detected by MUSE in deep fields. We use this simulation to study the origin and dynamics of the high-redshift circum-galactic medium (CGM). We find that the majority of the mass in the diffuse CGM is comprised of material infalling for the first time towards the halo center, but with the inner CGM also containing a comparable amount of mass that has moved past first-pericentric passage, and is in the process of settling into a rotationally supported configuration. Making the connection to Lyman alpha emission, we find that the observed extended surface brightness profile is due to a combination of three components: scattering of galactic Lyman alpha emission in the CGM, in-situ emission of CGM gas (mostly infalling), and Lyman alpha emission from small satellite galaxies. The weight of these contributions vary with distance from the galaxy such that (1) scattering dominates the inner regions (r < 7 kpc), at surface brightness larger than a few 10^-19 cgs, (2) all components contribute equally around r ~ 10 kpc (or SB ~10^-19), and (3) the contribution of small satellite galaxies takes over at large distances (or SB ~10^-20). Our simulation fails to reproduce the characteristic observed Lyman alpha spectral morphology that is red-shifted with respect to the systemic velocity, with the implication that the simulation is missing an important component of neutral outflowing gas.
A New Smart Approach for Best Location Determination Based on Internet of Things

Finding the best location among several alternatives require more effort, time, and devices in the usual cases, especially if these locations in another city or governorate. This study pursuit using a smart approach to select the best new primary school site with an accurate result in a short time and low cost. The presented approach utilizes a smartphone as an internet of things (IoT) device that has an internal Global Positioning System (GPS) unit to collect and send the location (GPS coordinates) via Google maps application to urban planners (decision-makers) to give their opinion in each site sent to them after making a spatial analysis for these site using the Arc GIS program to assess every advised site with each criterion. Then, the fuzzy TOPSIS method aggregates urban planners’ opinions to determine the more suitable site for a new primary school. The Fuzzy TOPSIS method was implemented using python code to reduce the time required for manual computation. All the Fuzzy TOPSIS steps executed time does not exceed 1 minute, and it just needs to enter the number of (criteria, decision-makers, and alternative sites). The importance weight of the criteria for each decision-maker and the ratings of alternative sites by the decision-makers’ chosen criteria. So with this smart approach, with a few hours, we can find a more fitting new site, although it took more than a week in the normal way.
Building communication networks: on the application of the Kruskal’s algorithm in the problems of large dimensions

The paper deals with the development of the topology of ultra-large communication networks, i.e. networks containing several thousand vertices. In this case, the coordinates of the vertices of the undirected graph are somehow predetermined and a set of edges must be constructed. The main point of the options we are considering for developing the network topology is the minimum of the sum of weights of the edges; however, we note in advance that this criterion of minimality is often not the only objective function in the practical problems we are considering. In our previous papers, two realistically considered tasks were formulated. However, everything is not so simple, and we cannot use the direct version of Kruskal’s algorithm. The complexity of this algorithm depends on the representation of the data, i.e. the data structures used. In our situation (when the number of considered vertices is approximately 5000 to 10000), the operation of a simple version of the algorithm takes about a half an hour, which, of course, is acceptable for a one-time solution to the problem under consideration, but it is unacceptable in the case when such solutions are constructed repeatedly (in particular, iteratively). Some temporary improvements to the practical operation of the algorithm provide different options for using complex data structures. The subject of this article can be formulated as follows. We are moving from exact algorithms (in particular, Kruskal’s algorithm) to some heuristics. Moreover, for the starting problem that we are considering, we cannot work without heuristic algorithm at all. However, we describe two specific variants of a simple implementation of Kruskal’s algorithm for problems of large dimensions; in our titles, those are “the 1st and the 2nd algorithms of the usual implementation”. We have formulated two heuristics (“the 3rd and 4th algorithms”). In our opinion, one of these algorithms turned out to be quite acceptable; we present some practical results of computational experiments. And it is very important that these two heuristics will be useful not only for such a “0-th problem”, but also for much more complex problems.
Design and Development of an Automatic Unmanned Railway Level Crossing Gate

In rapidly developing countries like India, Railways are an important mode of transportation among all the people. In the railway sector, the level crossing gate plays a vital role, which should be taken into consideration. But in the level crossing gates, due to poor monitoring by the humans, many accidents are happening day-by-day. So, there is a need to develop technology to solve this issue. This paper deals with the automatic railway gate at the level crossing, which replaces the gates operated by the gatekeepers. By making it in an automatic way, can reduce the time consumption for closing the gate and also reduces human power. Streamlined the working of level crossing gate through a mini prototype model that solves this problem. Here the sensor is placed safely near the level crossing gate, which is kept at a certain distance in the railway track. Whenever the train is fastened in the railway track, the vibrations which are produced during its motion are being sensed by a sensor and it provides the necessary signal pulses to the controller which is kept at the level crossing column setup. Then the controller activates the motor, therefore the gate closes and opens automatically. Visualized the design calculation for making this setup. Hence by implementing this idea, can able to control the accidents in unmanned areas, therefore the precious human life can be saved.
Ab initio
 based models for temperature-dependent magnetochemical interplay in bcc Fe-Mn alloys

Body-centered cubic (bcc) Fe-Mn systems are known to exhibit a complex and atypical magnetic behavior from both experiments and 0 K electronic-structure calculations, which is due to the half-filled $3d$ band of Mn. We propose effective interaction models for these alloys, which contain both atomic-spin and chemical variables. They were parameterized on a set of key density functional theory (DFT) data, with the inclusion of noncollinear magnetic configurations being indispensable. Two distinct approaches, namely a knowledge-driven and a machine-learning approach have been employed for the fitting. Employing these models in atomic Monte Carlo simulations enables the prediction of magnetic and thermodynamic properties of the Fe-Mn alloys, and their coupling, as functions of temperature. This includes the decrease of Curie temperature with increasing Mn concentration, the temperature evolution of the mixing enthalpy, and its correlation with the alloy magnetization. Also, going beyond the defect-free systems, we determined the binding free energy between a vacancy and a Mn atom, which is a key parameter controlling the atomic transport in Fe-Mn alloys.
Myosin cross-bridge kinetics slow at longer muscle lengths during isometric contractions in intact soleus from mice

Muscle contraction results from force-generating cross-bridge interactions between myosin and actin. Cross-bridge cycling kinetics underlie fundamental contractile properties, such as active force production and energy utilization. Factors that influence cross-bridge kinetics at the molecular level propagate through the sarcomeres, cells and tissue to modulate whole-muscle function. Conversely, movement and changes in the muscle length can influence cross-bridge kinetics on the molecular level. Reduced, single-molecule and single-fibre experiments have shown that increasing the strain on cross-bridges may slow their cycling rate and prolong their attachment duration. However, whether these strain-dependent cycling mechanisms persist in the intact muscle tissue, which encompasses more complex organization and passive elements, remains unclear. To investigate this multi-scale relationship, we adapted traditional step-stretch protocols for use with mouse soleus muscle during isometric tetanic contractions, enabling novel estimates of length-dependent cross-bridge kinetics in the intact skeletal muscle. Compared to rates at the optimal muscle length (Lo), we found that cross-bridge detachment rates increased by approximately 20% at 90% of Lo (shorter) and decreased by approximately 20% at 110% of Lo (longer). These data indicate that cross-bridge kinetics vary with whole-muscle length during intact, isometric contraction, which could intrinsically modulate force generation and energetics, and suggests a multi-scale feedback pathway between whole-muscle function and cross-bridge activity.
Adaptations to light contribute to the ecological niches and evolution of the terrestrial avifauna

The role of light in structuring the ecological niche remains a frontier in understanding how vertebrate communities assemble and respond to global change. For birds, eyes represent the primary external anatomical structure specifically evolved to interpret light, yet eye morphology remains understudied compared to movement and dietary traits. Here, I use Stanley Ritland's unpublished measurements of transverse eye diameter from preserved specimens to explore the ecological and phylogenetic drivers of eye morphology for a third of terrestrial avian diversity (N = 2777 species). Species with larger eyes specialized in darker understory and forested habitats, foraging manoeuvres and prey items requiring long-distance optical resolution and were more likely to occur in tropical latitudes. When compared to dietary and movement traits, eye size was a top predictor for habitat, foraging manoeuvre, diet and latitude, adding 8–28% more explanatory power. Eye size was phylogenetically conserved (λ = 0.90), with phylogeny explaining 61% of eye size variation. I suggest that light has contributed to the evolution and assembly of global vertebrate communities and that eye size provides a useful predictor to assess community response to global change.
Influence of prey availability on web-building in the social spider Stegodyphus sarasinorum (Araneae: Eresidae)

Abstract. Spider webs are characteristic of a species, yet web architecture, the amount of silk laid, and silk mechanics are plastic at an individual level. These different web parameters are influenced by the spiders' own intrinsic state as well as biotic and abiotic conditions. When compared to satiated spiders, hungry spiders are known to build bigger webs, alter the mesh width of the web or increase the frequency of web-building. Although the influence of hunger on web architecture is known in solitary spiders, it has not been studied in social spiders. Here, we examine how prey availability affects the amount of web and cribellate silk laid in the social spider Stegodyphus sarasinorum, Karsch, 1892 (Eresidae). In a laboratory setup, we observed that unfed spiders invest more in web-building, compared to fed spiders. Unfed social spider colonies laid more silk, particularly cribellate silk, than fed colonies. Our results help to shed light on the plasticity of web architecture in social spiders with respect to changes in prey availability.
Influence of Poly(L-lactic acid) Molecular Weight on the Encapsulation Efficiency of Urea in Microcapsule Using a Simple Solvent Evaporation Technique

ABSTRACT Poly(L-lactic acid) microencapsulated urea was prepared in water-in-oil-in-water (W1/O/W2) system by the solvent evaporation technique. The influence of poly(L-lactic acid) molecular weight on the percent loading, encapsulation efficiency, and the microcapsule morphology was studied using poly(L-lactic acid) having different number average molecular weights (Mn). Using the higher Mn, the smoother shell with complete encapsulation microcapsules was formed. Moreover, the percent loading and encapsulation efficiency of urea also increased with the poly(L-lactic acid) molecular weight. At 80,000 g/mol of poly(L-lactic acid), the obtained microcapsule gave the highest both percent loading (32%) and encapsulation efficiency (56%). The urea control release study of the prepared microcapsules was implemented by in vitro testing. The encapsulated urea was gradually released from the microcapsules, approximately 53, 29, and 22% of poly(L-lactic acid) at 3,000, 30,000, and 80,000 g/mol, respectively, for a month. These results presented the possibility of the prepared poly(L-lactic acid) microcapsules-encapsulated urea for urea control release that could be utilized in agricultural applications. GRAPHICAL ABSTRACT
Boundaries of Flow Table Usage Reduction Algorithms Based on Elephant Flow Detection

The majority of Internet traffic is caused by a relatively small number of flows (so-called elephant flows). This phenomenon can be exploited to facilitate traffic engineering: resource-costly individual flow forwarding entries can be created only for elephants while serving mice over the shortest paths. Although this idea already appeared in proposed TE systems, it was not examined by itself. It remains unknown what extent of flow table occupancy and operations number reduction can be achieved or how to select thresholds or sampling rates to cover the desired fraction of traffic. In this paper, we use reproducible traffic models obtained from a 30-day-long campus trace covering 4 billion flows, to answer these questions. We establish theoretical boundaries for flow table usage reduction algorithms that classify flows since the first packet, after reaching a predefined counter threshold or detect elephants by sampling. An important finding is that simple packet sampling performs surprisingly well on realistic traffic, reducing the number of flow entries by a factor up to 400, still covering 80% of the traffic. We also provide an open-source software package allowing the replication of our experiments or the performing of similar evaluations for other algorithms or flow distributions.
Fundamental Limits of Controlled Stochastic Dynamical Systems: An Information-Theoretic Approach

In this paper, we examine the fundamental performance limitations in the control of stochastic dynamical systems; more specifically, we derive generic $\mathcal{L}_p$ bounds that hold for any causal (stabilizing) controllers and any stochastic disturbances, by an information-theoretic analysis. We first consider the scenario where the plant (i.e., the dynamical system to be controlled) is linear time-invariant, and it is seen in general that the lower bounds are characterized by the unstable poles (or nonminimum-phase zeros) of the plant as well as the conditional entropy of the disturbance. We then analyze the setting where the plant is assumed to be (strictly) causal, for which case the lower bounds are determined by the conditional entropy of the disturbance. We also discuss the special cases of $p = 2$ and $p = \infty$, which correspond to minimum-variance control and controlling the maximum deviations, respectively. In addition, we investigate the power-spectral characterization of the lower bounds as well as its relation to the Kolmogorov-Szeg\"o formula.
Cerebellar projections to the macaque midbrain tegmentum: Possible near response connections

Abstract Since most gaze shifts are to targets that lie at a different distance from the viewer than the current target, gaze changes commonly require a change in the angle between the eyes. As part of this response, lens curvature must also be adjusted with respect to target distance by the ciliary muscle. It has been suggested that projections by the cerebellar fastigial and posterior interposed nuclei to the supraoculomotor area (SOA), which lies immediately dorsal to the oculomotor nucleus and contains near response neurons, support this behavior. However, the SOA also contains motoneurons that supply multiply innervated muscle fibers (MIFs) and the dendrites of levator palpebrae superioris motoneurons. To better determine the targets of the fastigial nucleus in the SOA, we placed an anterograde tracer into this cerebellar nucleus in Macaca fascicularis monkeys and a retrograde tracer into their contralateral medial rectus, superior rectus, and levator palpebrae muscles. We only observed close associations between anterogradely labeled boutons and the dendrites of medial rectus MIF and levator palpebrae motoneurons. However, relatively few of these associations were present, suggesting these are not the main cerebellar targets. In contrast, labeled boutons in SOA, and in the adjacent central mesencephalic reticular formation (cMRF), densely innervated a subpopulation of neurons. Based on their location, these cells may represent premotor near response neurons that supply medial rectus and preganglionic Edinger–Westphal motoneurons. We also identified lens accommodation-related cerebellar afferent neurons via retrograde trans-synaptic transport of the N2c rabies virus from the ciliary muscle. They were found bilaterally in the fastigial and posterior interposed nuclei, in a distribution which mirrored that of neurons retrogradely labeled from the SOA and cMRF. Our results suggest these cerebellar neurons coordinate elements of the near response during symmetric vergence and disjunctive saccades by targeting cMRF and SOA premotor neurons.
Modelling laminar flame using simple chemical reacting system

The objective of my thesis work is to model laminar diffusion flame using simple chemical reacting system (SCRS) combustion model. This combustion model assumes that the chemical reactions are infinitely fast and take place via a global one-step without intermediate reactions. The detailed kinetics is considered unimportant as this model is concerned with the global nature of the combustion process and with the final major species concentration. The model is developed using C++ computer language. The algorithm used for solving Navier-stokes and mixture fraction equations is the fractional step method for compressible flow with low Mach number. Low Mach number approximation is used in simplifying the flow equations as flow speed is very low compared to speed of sound. By modelling diffusion flame through an SCRS, flame temperature and species concentration are retrieved from mixture fraction field. The thesis is divided into six chapters. Chapter 1 is an introductory chapter about objective, scope and justification of the work. In Chapter 2 the conservation laws of fluid motion are explained. In chapter 3, the discretization of the computational domain and discretization of different terms in the transport equations are explained. The fractional step method algorithm for incompressible flow and compressible flow with low Mach number are illustrated in chapter 4.In chapter 5, the code is verified for incompressible flow by the method of manufactured solution (MMS) and by comparing code results with benchmark solutions of driven cavity and differentially heated cavity for incompressible flow, while for compressible flow code result is compared with benchmark solution of differentially heated cavity with high temperature difference. In chapter 6 SCRS model is discussed and the simulation results for diluted methane diffusion flame are presented. The simulation results for the laminar diffusion flame show that the flame reaches its maximum temperature at the stoichiometric mixture fraction contour line where oxygen and fuel are completely consumed. The flame length is changed by altering fuel or oxidant streams velocities. Also changing the percentage of nitrogen gas in the fuel and oxidant stream affect both flame length and flame maximum temperature.
Using Mobile Apps to Combat Fake News

Abstract Librarians and library professionals should challenge themselves to seek the most unbiased and truthful health news and information during a pandemic that has many patrons misled by fake news, disinformation, and misinformation. Through the use of mobile apps users can start to discern truth from lies, and users can learn how to more readily spot fake news. Mobile news apps also have advanced in their features, allowing users to share credible stories to stop the spread of fake news and disinformation and become part of the story by aiding in fact-checking, up-voting, and reporting false, misleading and biased news articles.
DONeRF: Towards Real‐Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networks

The recent research explosion around implicit neural representations, such as NeRF, shows that there is immense potential for implicitly storing high‐quality scene and lighting information in compact neural networks. However, one major limitation preventing the use of NeRF in real‐time rendering applications is the prohibitive computational cost of excessive network evaluations along each view ray, requiring dozens of petaFLOPS. In this work, we bring compact neural representations closer to practical rendering of synthetic content in real‐time applications, such as games and virtual reality. We show that the number of samples required for each view ray can be significantly reduced when samples are placed around surfaces in the scene without compromising image quality. To this end, we propose a depth oracle network that predicts ray sample locations for each view ray with a single network evaluation. We show that using a classification network around logarithmically discretized and spherically warped depth values is essential to encode surface locations rather than directly estimating depth. The combination of these techniques leads to DONeRF, our compact dual network design with a depth oracle network as its first step and a locally sampled shading network for ray accumulation. With DONeRF, we reduce the inference costs by up to 48× compared to NeRF when conditioning on available ground truth depth information. Compared to concurrent acceleration methods for raymarching‐based neural representations, DONeRF does not require additional memory for explicit caching or acceleration structures, and can render interactively (20 frames per second) on a single GPU.