Miracle-dz/UniFAR-FTUs huggingface dataset:
Dark matter capture in celestial objects: light mediators, self-interactions, and complementarity with direct detection

We generalize the formalism for DM capture in celestial bodies to account for arbitrary mediator mass, and update the existing and projected astrophysical constraints on DM-nucleon scattering cross section from observations of neutron stars. We show that the astrophysical constraints on the DM-nucleon interaction strength, that were thought to be the most stringent, drastically weaken for light mediators and can be completely voided. For asymmetric DM, existing astrophysical constraints are completely washed out for mediators lighter than 5 MeV, and for annihilating DM the projected constraints are washed out for mediators lighter than 0.25 MeV. Related terrestrial direct detection bounds also weaken, but in a complementary fashion; they supersede the astrophysical capture bounds for small or large DM mass, respectively for asymmetric or annihilating DM. Repulsive self-interactions of DM have an insignificant impact on the total capture rate, but a significant impact on the black hole formation criterion. This further weakens the constraints on DM-nucleon interaction strength for asymmetric self-repelling DM, whereas constraints remain unaltered for annihilating self-repelling DM. We use the correct Hawking evaporation rate of the newly formed black hole, that was approximated as a blackbody in previous studies, and show that, despite a more extensive alleviation of collapse as a result, the observation of a neutron star collapse can probe a wide range of DM self-interaction strengths.
Curve Fitting in Raman and IR Spectroscopy: Basic Theory of Line Shapes and Applications

The basic theory behind the origin of line shape is presented and applied to curve fitting. This understanding should enable a user to apply with precision the Peak Resolve routine of OMNICTM. The affect of the line shape parameters on the curve fitting is discussed and a set of literature references is provided for more intense investigation. The scope of this technical note is limited to the basic theory behind vibrational (IR and Raman) line shapes and how this applies to curve fitting. There are many phenomena, like Fermi Resonance and collision-induced scattering, which affect vibrational line shapes; the reader is directed to the references cited for more information.
Classification-assisted Query Processing for Network Telemetry

—Network telemetry systems are responsible for providing operators with the necessary information to secure and manage a network. As such, they should be able to respond, in real-time, to a number of queries on events ranging from performance impairments to attacks. While existing measurement techniques can swiftly collect all the relevant data from high-speed trafﬁc streams, signiﬁcant processing costs are faced when aggregating and evaluating such data to generate elaborate query responses. This paper explores the use of machine-learning approaches for reducing the run-time processing cost of monitoring queries. A novel processing workﬂow is introduced, which entails classiﬁers trained over recent trafﬁc, automatically tuned to match accuracy requirements of query responses, and applied to sampled subsets of raw measurement data. Experiments with representative monitoring queries on recent CAIDA trafﬁc traces demonstrate promising improvements on the query processing capability, by up to 3x, while maintaining accuracy levels above 98%.
Memory-Efficient Data Structures for Learning and Prediction

In many real-world machine learning systems, memory efficiency, data pipeline speed, and prediction latency are paramount. Here, we introduce two data structures—already in production in industrial machine learning settings—that aim to address these practical needs. EdgeFrame is a data frame optimized for memory-efficient machine learning on industrial data. It supports lightweight views that reuse the same components to minimize memory footprints. An EdgeFrame and Columns can be forked (with copy-on-write semantics) so that several components of a data pipeline can share the same data while avoiding side effects caused by local modifications. An EdgeFrame can be stored off-heap so it can be shared among multiple worker processes on the same machine. EdgeFrame can also be stored out-of-core so data sets larger than RAM can be handled. EdgeFrame supports arrays as a first-class data type so that image and sensor data can easily be represented in the same data set. We also introduce and motivate the representation of machine learning models in a parse-free format, allowing intelligent use of I/O bandwidth when loaded from disk. This greatly decreases the time to first prediction when the models are pulled from cold storage.
Introduction: Changing Tourism in the Cities of Post-communist Central and Eastern Europe

ABSTRACT This special edition examines various aspects of urban tourism in the post-communist cities of Central and Eastern Europe (CEE). It begins by examining the nature of tourism restructuring in the region since the end of communism and the way that this unfolds in cities. It then examines major global changes in the nature of tourism and their impacts on urban tourism in CEE. These include the growing demand among tourists for new experiences and destinations; the impact of budget airlines on tourism in smaller cities; the impacts of the sharing economy (particularly Airbnb); and the growing emphasis on events and festivals as a means of attracting visitors to cities. The article ends by introducing the six articles that make up this special edition.
Secured Real Estate Transactions using Blockchain Technology

---------------------------------------------------------------------***---------------------------------------------------------------------- Abstract - The Real Estate is facing a lot of problems including the trust issues, the path of how data shared and lot of automatic process. There are many organization agents, e-commerce websites and various other channels through which people can search a property for buying, leasing or putting their own property up for sale. The real estate by name itself has a lack of trust and transparency in data and record management. The public land title records are maintained in a local space, and the lenders need to contact the relevant local entities for each title assurance process, hence the maintenance cost of asset data from a transactional perspective is high and its required to maintain a title and search for public records which contribute to delay and higher costs . A solution for monitoring and transferring properties in a secure way can drastically reduce title search, examination time and costs. Block chain is a decentralized data management and transaction solution, has the potential to address many of the challenges faced by this industry
A Case for Hardware-Based Demand Paging

The virtual memory system is pervasive in today’s computer systems, and demand paging is the key enabling mechanism for it. At a page miss, the CPU raises an exception, and the page fault handler is responsible for fetching the requested page from the disk. The OS typically performs a context switch to run other threads as traditional disk access is slow. However, with the widespread adoption of high-performance storage devices, such as low-latency solid-state drives (SSDs), the traditional OS-based demand paging is no longer effective because a considerable portion of the demand paging latency is now spent inside the OS kernel. Thus, this paper makes a case for hardware-based demand paging that mostly eliminates OS involvement in page miss handling to provide a near-disk-access-time latency for demand paging. To this end, two architectural extensions are proposed: LBA-augmented page table that moves I/O stack operations to the control plane and Storage Management Unit that enables CPU to directly issue I/O commands without OS intervention in most cases. OS support is also proposed to detach tasks for memory resource management from the critical path. The evaluation results using both a cycle-level simulator and a real x86 machine with an ultra-low latency SSD show that the proposed scheme reduces the demand paging latency by 37.0%, and hence improves the performance of FIO read random benchmark by up to 57.1% and a NoSQL server by up to 27.3% with real-world workloads. As a side effect of eliminating OS intervention, the IPC of the user-level code is also increased by up to 7.0%.
Exploring Spatial Membrane Tensegrity Shell Structures

Structural membranes exhibit advantages over slab and frame structures, accommodating large deformations while still elegantly combining spatial enclosure with material efficiency. One of the most promising types of membrane structures are membrane tensegrity structures, which are composed of discontinuous struts embedded in a tensile membrane. To date, membrane tensegrity structures are limited to completely closed formations or require extensive tethering, hindering their applicability for diverse architectural contexts. Here, a design framework is presented for creating self-supporting membrane tensegrity shell structures with spatial openings, enabled by novel reciprocally tessellated strut configurations. Through a combination of heuristic physical prototyping and digital formfinding tools, a library of membrane tensegrity forms has been developed that serves as tangible data for an expanded morphospace. To test the effectiveness of the established methods, a 10 m2 membrane tensegrity shell pavilion was built as a first large-scale demonstrator. Feedback from this demonstrator led to the development of computational strut tessellation tools that enable the search for informed, performance-driven design space.
Evidence for supernova feedback sustaining gas turbulence in nearby star-forming galaxies

It is widely known that the gas in galaxy discs is highly turbulent, but there is much debate on which mechanism can energetically maintain this turbulence. Among the possible candidates, supernova (SN) explosions are likely the primary drivers but doubts remain on whether they can be sufficient in regions of moderate star formation activity, in particular in the outer parts of discs. Thus, a number of alternative mechanisms have been proposed. In this paper, we measure the SN efficiency η, namely the fraction of the total SN energy needed to sustain turbulence in galaxies, and verify that SNe can indeed be the sole driving mechanism. The key novelty of our approach is that we take into account the increased turbulence dissipation timescale associated with the flaring in outer regions of gaseous discs. We analyse the distribution and kinematics of HI and CO in ten nearby star-forming galaxies to obtain the radial profiles of the kinetic energy per unit area for both the atomic gas and the molecular gas. We use a theoretical model to reproduce the observed energy with the sum of turbulent energy from SNe, as inferred from the observed star formation rate (SFR) surface density, and the gas thermal energy. For the atomic gas, we explore two extreme cases in which the atomic gas is made either of cold neutral medium or warm neutral medium, and the more realistic scenario with a mixture of the two phases. We find that the observed kinetic energy is remarkably well reproduced by our model across the whole extent of the galactic discs, assuming η constant with the galactocentric radius. Taking into account the uncertainties on the SFR surface density and on the atomic gas phase, we obtain that the median SN efficiencies for our sample of galaxies are ⟨ηatom⟩ = 0.015−0.008+0.018 for the atomic gas and ⟨ηmol⟩ = 0.003−0.002+0.006 for the molecular gas. We conclude that SNe alone can sustain gas turbulence in nearby galaxies with only few percent of their energy and that there is essentially no need for any further source of energy.
A Methodology for Assessing the Environmental Effects Induced by ICT Services: Part I: Single Services

Information and communication technologies (ICT) are increasingly seen as key enablers for climate change mitigation measures. They can make existing products and activities more efficient or substitute them altogether. Consequently, different initiatives have started to estimate the environmental effects of ICT services. Such assessments, however, lack scientific rigor and often rely on crude assumptions and methods, leading to inaccurate or even misleading results. The few methodological attempts that exist do not address several crucial aspects, and are thus insufficient to foster good assessment practice. Starting from such a high-level standard from the European Telecommunication Standardisation Institute (ETSI) and the International Telecommunication Union (ITU), this article identifies the shortcomings of existing methodologies and proposes solutions. It addresses several aspects for the assessment of single ICT services: the goal and scope definition (analyzing differences between ICT substitution and optimization, the time perspective of the assessment, the challenge of a hypothetical baseline for the situation without the ICT solution, and the differences between modelling and case studies) as well as the often-ignored influence of rebound effects and the difficult extrapolation from case studies to larger populations.
A Global Nonhydrostatic Atmospheric Model with a Mass- and Energy-conserving Vertically Implicit Correction (VIC) Scheme

Global nonhydrostatic atmospheric models are becoming increasingly important for studying the climates of planets and exoplanets. However, such models suffer from computational difficulties due to the large aspect ratio between the horizontal and vertical directions. To overcome this problem, we developed a global model using a vertically implicit correction (VIC) scheme in which the integration time step is no longer limited by the vertical propagation of acoustic waves. We proved that our model, based on the Athena++ framework and its extension for planetary atmospheres—SNAP (Simulating Nonhydrostatic Atmospheres on Planets), rigorously conserves mass and energy in finite-volume simulations. We found that traditional numerical stabilizers such as hyperviscosity and divergence damping are not needed when using the VIC scheme, which greatly simplifies the numerical implementation and improves stability. We present simulation results ranging from 1D linear waves to 3D global circulations with and without the VIC scheme. These tests demonstrate that our formulation correctly tracks local turbulent motions, produces Kelvin–Helmholtz instability, and generates a super-rotating jet on hot Jupiters. Employing this VIC scheme improves the computational efficiency of global simulations by more than two orders of magnitude compared to an explicit model and facilitates the capability of simulating a wide range of planetary atmospheres both regionally and globally.
Gradient descent follows the regularization path for general losses

Recent work across many machine learning disciplines has highlighted that standard descent methods, even without explicit regularization, do not merely minimize the training error, but also exhibit an implicit bias. This bias is typically towards a certain regularized solution, and relies upon the details of the learning process, for instance the use of the cross-entropy loss. In this work, we show that for empirical risk minimization over linear predictors with arbitrary convex, strictly decreasing losses, if the risk does not attain its infimum, then the gradient-descent path and the algorithm-independent regularization path converge to the same direction (whenever either converges to a direction). Using this result, we provide a justification for the widely-used exponentially-tailed losses (such as the exponential loss or the logistic loss): while this convergence to a direction for exponentially-tailed losses is necessarily to the maximum-margin direction, other losses such as polynomially-tailed losses may induce convergence to a direction with a poor margin.
Preliminary results from characterization of the Iberian Peninsula sturgeon based on analysis of the mtDNA cytochrome b

Historically, the Atlantic sturgeon Acipenser sturio L. , 1758 was considered the only sturgeon species that inhabited rivers of the Iberian Peninsula. Nevertheless, in a recent paper, GarridoRamos et al. (1997) identified specimen EBD 8174 (museum collection of the Donana Biological Station, Spain), from the Guadalquivir River, as the Adriatic sturgeon Acipenser naccarii Bonaparte, 1836, suggesting that both A. sturio and A. naccarii could be native to Spain. To test this theory, we compared partial mitochondrial cytochrome b (cyt b) gene sequences obtained from museum specimens of A. sturio that originated from the Iberian Peninsula, the Adriatic and the North Sea, as well as from live individuals of the Gironde River population in France. Specimens of A. naccarii and of the Siberian sturgeon Acipenser baerii Brandt, 1869 from fish farms were also included in the study. DNA from museum specimens was successfully amplified using the protocol of France and Kocher (1996) for DNA extraction from formalin-fixed and ethanol-preserved samples. Phylogenetic analysis was performed on partial cyt b gene sequences (over 402-bp and 245-bp). We identified specimen EBD 8174 as A. sturio, confirming the opinion that A. sturio is the only sturgeon species of the Iberian Peninsula. Further molecular analyses of museum specimens are needed for a description of the historical intraspecies genetic variation within A. sturio. This information is crucial for any future recovery plan for this species. Our comparison also showed interspecies sequence divergence ranging from 6.91 % (A. sturio/A. naccarii) to 7.43 % (A. sturio/A. baerii).
Small intestinal CD8 + TCRγδ + NKG2A + intraepithelial lymphocytes have attributes of regulatory cells in patients with celiac disease

Intraepithelial lymphocytes (IELs) bearing the γδ TCR are more abundant in the small intestinal mucosa of patients with celiac disease (CD) compared with healthy individuals. However, their role in disease pathogenesis is not well understood. Here, we investigated the functional attributes of TCRγδ+ IELs isolated from intestinal biopsies of patients with either active celiac disease (ACD) or those on a gluten-free diet (GFD). We found that compared with individuals with ACD, individuals on GFD have a higher frequency of CD8+TCRγδ+ IELs that express the inhibitory NK receptor NKG2A and intracellular TGF-β1. TCR triggering as well as cross-linking of NKG2A increased both TGF-β1 intracellular expression and secretion in vitro. Coculture of sorted TCRγδ+NKG2A+ IELs, IL-15–stimulated TCRαβ+ IELs, and HLA-E+ enterocytes resulted in a decreased percentage of cytotoxic CD8+TCRαβ+ IELs expressing intracellular IFN-γ and granzyme-B and surface NKG2D. This inhibition was partially abrogated by blocking either TGF-β alone or both NKG2A and HLA-E. Thus, our data indicate that suppression was at least partially mediated by TGF-β secretion as a result of engagement of NKG2A with its ligand, HLA-E, on enterocytes and/or TCRαβ+ IELs. These findings demonstrate that human small intestinal CD8+TCRγδ+ IELs may have regulatory potential in celiac disease.
Environmental Dependence of Self-regulating Black Hole Feedback in Massive Galaxies

In the universe’s most massive galaxies, active galactic nucleus (AGN) feedback appears to limit star formation. The accumulation of cold gas near the central black hole fuels powerful AGN outbursts, keeping the ambient medium in a state marginally unstable to condensation and formation of cold gas clouds. However, the ability of that mechanism to self-regulate may depend on numerous environmental factors, including the depth of the potential well and the pressure of the surrounding circumgalactic medium (CGM). Here we present a suite of numerical simulations, with halo mass ranging from 2 × 1012 M⊙ to 8 × 1014 M⊙, exploring the dependence of AGN feedback on those environmental factors. We include the spatially extended mass and energy input from the massive galaxy’s old stellar population capable of sweeping gas out of the galaxy if the confining CGM pressure is sufficiently low. Our simulations show that this feedback mechanism is tightly self-regulating in a massive galaxy with a deep central potential and low CGM pressure, permitting only small amounts of multiphase gas to accumulate and allowing no star formation. In a similar-mass galaxy with shallower central potential and greater CGM pressure the feedback mechanism is more episodic, producing extended multiphase gas and allowing small rates of star formation (∼0.1 M⊙ yr−1). At the low-mass end, the mechanism becomes implausibly explosive, perhaps because the CGM initially has no angular momentum, which would have reduced the amount of condensed gas capable of fueling feedback.
The impact of fine-scale turbulence on phytoplankton community structure

We examined the effect of fine-scale fluid turbulence on phytoplankton community structure in an idealized, size-structured community model. It has been shown that turbulence can enhance nutrient transport toward a cell, particularly for larger cells in highly turbulent conditions. Our model suggests that under weak grazing pressure the effect of this mechanism on relative phytoplankton fitness and community structure is negligible. Under these conditions, the high nutrient affinity of small cells dominates relative fitness and allows them to outcompete larger cells. In contrast, when grazing pressure is strong, the turbulent enhancement of nutrient uptake and fitness for larger cells can become ecologically significant. Here, increasing turbulence broadens the size range of coexisting phytoplankton and increases the size of the dominant cell type at equilibrium. We also estimate and map open ocean turbulent dissipation rates as a function of climatological surface wind stresses. The turbulent enhancement of nutrient uptake is most likely to be ecologically significant in regions with low nutrient levels, strong grazing pressure, and relatively high turbulence, such as in windier portions of the subtropical gyre or post-bloom conditions at higher latitudes. In these regions, turbulence may help sustain larger cell populations through otherwise unfavorable environmental conditions.
On the Principle of Accountability: Challenges for Smart Homes & Cybersecurity

This chapter introduces the Accountability Principle and its role in data protection governance. We focus on what accountability means in the context of cybersecurity management in smart homes, considering the EU General Data Protection Law requirements to secure personal data. This discussion sits against the backdrop of two key new developments in data protection law. Firstly, the law is moving into the home, due to narrowing of the so called household exemption. Concurrently, household occupants may now have legal responsibilities to comply with the GDPR, as they find themselves jointly responsible for compliance, as they are possibly held to determine the means and purposes of data collection with IoT device vendors. As a complex socio-technical space, we consider the interactions between accountability requirements and the competencies of this new class of domestic data controllers (DDCs). Specifically, we consider the value and limitations of edge-based security analytics to manage smart home cybersecurity risks, reviewing a range of prototypes and studies of their use. We also reflect on interpersonal power dynamics in the domestic setting e.g. device control; existing social practices around privacy and security management in smart homes; and usability issues that may hamper DDCs ability to rely on such solutions. We conclude by reflecting on 1) the need for collective security management in homes and 2) the increasingly complex divisions of responsibility in smart homes between device users, account holders, IoT device/software/firmware vendors, and third parties.