Miracle-dz/UniFAR-FTUs huggingface dataset:
Dark energy, the swampland, and the equivalence principle

It has recently been argued that string theory does not admit de Sitter vacua. This would imply that the current accelerated expansion of the universe is not driven by a cosmological constant (or vacuum energy) but by other means such as a quintessential scalar field. Such a scalar field is in general expected to couple to at least some matter species, such as dark matter. Cosmological observations already constrain such dark matter couplings strongly. We argue that there are a number of interesting scenarios to be explored, such as coupling functions which possess a minimum at finite field values. In these theories, the effective gravitational coupling between dark matter particles grows with time and are consistent with observations of the anisotropies in the cosmic microwave background radiation and large scale structures. We argue that such couplings might also help to alleviate the tension between the swampland conjectures and the properties of the quintessential potential. Observational signatures of violations of the equivalence principle in the dark sector are expected in the non-linear regime on intermediate or small scales.
Simulations of flux variability of oscillating accretion fluid tori around Kerr black holes

Abstract High frequency quasi-periodic oscillations (HF QPOs) are observed in the X-ray power-density spectra (PDS) of several microquasars and low mass X-ray binaries. Many proposed QPO models are based on oscillations of accretion toroidal fluid structures orbiting in the vicinity of a compact object. We study oscillating accretion tori orbiting in the vicinity of a Kerr black hole. We demonstrate that significant variation of the observed flux can be caused by the combination of radial and vertical oscillation modes of a slender, polytropic, perfect fluid, non-self-graviting torus with constant specific angular momentum. We investigate two combinations of the oscillating modes corresponding to the direct resonance QPO model and the modified relativistic precession QPO model.
A note on the lower bound of black-hole area change in the tunneling formalism

In the framework of tunneling mechanism and employing Bekenstein's general expression for the variation of the black-hole area, we determine the area quantum up to a constant. Depending on the value of this constant one can get either Bekenstein's lower bound or Hod's one for the change in the black-hole area.
Indo-European Inroads into the Syntactic-Etymological Interface: A Reconstruction of the PIE verbal root *menkʷ- ‘to be short; to lack’ and its Argument Structure

: In this article we report a previously unidentified verbal root for the Indo-European protolanguage, * menk ʷ - ‘to be short; to lack’, based on verbal and nominal reflexes in Italic, Indo-Iranian, Germanic, Tocharian and Anatolian, founded, we claim, in the Caland System , an archaic stratum of the Proto-Indo-European derivational system. In four of five Indo-European subgroups, predicates are found occurring with a subject(-like) argument in a non-nominative case, dative in the languages that have retained the Indo- European case morphology, but an oblique case in the branches where different non-nom-inative forms have merged. The documented verbal forms cannot be unified into a single reconstructable verb, yet we argue that the more abstract argument structure construction involving a dative subject(-like) argument must be inherited from Proto-Indo-European. Hence, we suggest a partial reconstruction for the grammar of Proto-Indo-European, based on the attested Tocharian form, * m(e)nk ʷ - MP , the non-nominative case of the sub- ject(-like) argument, and the meaning ‘lack’. Taken together, this cumulative evidence corroborates the assumption that a verb meaning ‘lack’ developed from ‘be short’ in the proto-language, indeed instantiating a non-canonically case-marked argument structure with its subject(-like) argument in the dative case.
Contextualized Word Representations for Document Re-Ranking

Although considerable attention has been given to neural ranking architectures recently, far less attention has been paid to the term representations that are used as input to these models. In this work, we investigate how two pretrained contextualized language modes (ELMo and BERT) can be utilized for ad-hoc document ranking. Through experiments on TREC benchmarks, we find that several existing neural ranking architectures can benefit from the additional context provided by contextualized language models. Furthermore, we propose a joint approach that incorporates BERT's classification vector into existing neural models and show that it outperforms state-of-the-art ad-hoc ranking baselines. We also address practical challenges in using these models for ranking, including the maximum input length imposed by BERT and runtime performance impacts of contextualized language models.
Au 40 : A large tetrahedral magic cluster

40 is a magic number for tetrahedral symmetry predicted in both nuclear physics and the electronic jellium model. We show that Au${}_{40}$ could be such a a magic cluster from density functional theory-based basin hopping for global minimization. The putative global minimum found for Au${}_{40}$ has a twisted pyramid structure, reminiscent of the famous tetrahedral Au${}_{20}$, and a sizable HOMO-LUMO gap of 0.69 eV, indicating its molecular nature. Analysis of the electronic states reveals that the gap is related to shell closings of the metallic electrons in a tetrahedrally distorted effective potential.
On the Mass Function, Multiplicity, and Origins of Wide-orbit Giant Planets

A major outstanding question regarding the formation of planetary systems is whether wide-orbit giant planets form differently than close-in giant planets. We aim to establish constraints on two key parameters that are relevant for understanding the formation of wide-orbit planets: (1) the relative mass function and (2) the fraction of systems hosting multiple companions. In this study, we focus on systems with directly imaged substellar companions and the detection limits on lower mass bodies within these systems. First, we uniformly derive the mass probability distributions of known companions. We then combine the information contained within the detections and detection limits into a survival analysis statistical framework to estimate the underlying mass function of the parent distribution. Finally, we calculate the probability that each system may host multiple substellar companions. We find that (1) the companion mass distribution is rising steeply toward smaller masses, with a functional form of N ∝ M−1.3±0.03, and consequently, (2) many of these systems likely host additional undetected substellar companions. Combined, these results strongly support the notion that wide-orbit giant planets are formed predominantly via core accretion, similar to the better studied close-in giant planets. Finally, given the steep rise in the relative mass function with decreasing mass, these results suggest that future deep observations should unveil a greater number of directly imaged planets.
Multi-Armed Bandit for Energy-Efficient and Delay-Sensitive Edge Computing in Dynamic Networks With Uncertainty

In the edge computing paradigm, mobile devices offload the computational tasks to an edge server by routing the required data over the wireless network. The full potential of edge computing becomes realized only if a smart device selects the most appropriate server in terms of the latency and energy consumption, among many available ones. The server selection problem is challenging due to the randomness of the environment and lack of prior information about the same. Therefore, a smart device, which sequentially chooses a server under uncertainty, aims to improve its decision based on the historical time and energy consumption. The problem becomes more complicated in a dynamic environment, where key variables might undergo abrupt changes. To deal with the aforementioned problem, we first analyze the required time and energy to data transmission and processing. We then use the analysis to cast the problem as a budget-limited multi-armed bandit problem, where each arm is associated with a reward and cost, with time-variant statistical characteristics. We propose a policy to solve the formulated problem and prove a regret bound. The numerical results demonstrate the superiority of the proposed method compared to several online learning algorithms.
Random Trees: An Interplay between Combinatorics and Probability

Trees are a fundamental object in graph theory and combinatorics as well as a basic object for data structures and algorithms in computer science. During the last years research related to (random) trees has been constantly increasing and several asymptotic and probabilistic techniques have been developed in order to describe characteristics of interest of large trees in different settings. The aim of this book is to provide a thorough introduction into various aspects of trees in random settings and a systematic treatment of the involved mathematical techniques. It should serve as a reference book as well as a basis for future research. One major conceptual aspect is to bridge combinatorial and probabilistic methods that range from counting techniques (generating functions, bijections) over asymptotic methods (saddle point techniques, singularity analysis) to various sophisticated techniques in asymptotic probability (martingales, convergence of stochastic processes, concentration inequalities).
Application of optical fiber sensing technology in bridge detection

This paper introduces the development and application status of bridge detection technology at home and abroad, focuses on the research and application of optical fiber sensing technology in bridge detection at home and abroad, and takes strain detection as an example to introduce the detection principle, method and latest research of optical fiber sensing technology in bridge detection. Finally, the paper points out the development direction of optical fiber sensing technology in bridge detection.
A Survey on Wireless Wearable Body Area Networks: A Perspective of Technology and Economy

The deployment of wearable or body-worn devices is increasing rapidly, and thus researchers’ interests mainly include technical and economical issues, such as networking, interoperability, security, power optimization, business growth and regulation. To address these issues properly, previous survey papers usually focused on describing the wireless body area network architecture and network protocols. This implies that deployment issues and awareness issues of wearable and BAN devices are not emphasized in previous work. To defeat this problem, in this study, we have focused on feasibility, limitations, and security concerns in wireless body area networks. In the aspect of the economy, we have focused on the compound annual growth rate of these devices in the global market, different regulations of wearable/wireless body area network devices in different regions and countries of the world and feasible research projects for wireless body area networks. In addition, this study focuses on the domain of devices that are equally important to physicians, sportsmen, trainers and coaches, computer scientists, engineers, and investors. The outcomes of this study relating to physicians, fitness trainers and coaches indicate that the use of these devices means they would be able to treat their clients in a more effective way. The study also converges the focus of businessmen on the Annual Growth Rate (CAGR) and provides manufacturers and vendors with information about different regulatory bodies that are monitoring and regulating WBAN devices. Therefore, by providing deployment issues in the aspects of technology and economy at the same time, we believe that this survey can serve as a preliminary material that will lead to more advancements and improvements in deployment in the area of wearable wireless body area networks. Finally, we present open issues and further research direction in the area of wireless body area networks.
Fuzzy-Resilient Distributed Optimal Coordination for Nonlinear Multiagent Systems Under Command Attacks

In this article, we consider the problem of resilient distributed optimal coordination for uncertain nonlinear multiagent systems, where each agent is remotely dominated by an associated instruction generator via an unreliable network channel, which may be distorted by false data injection (FDI) attacks. To avoid evaluating the quality of decision variable or computing its high-order derivatives when applying the backstepping method, which is difficult in a distributed way, a new two-layer integrated design protocol with a fuzzy-approximation-based adaptive dynamics compensation mechanism is designed. Through the local online estimation of the optimal solution and design of adaptive feedback gain, the fuzzy adaptive mechanism realizes the mutual compensation of cyber dynamics and physical dynamics. Resultantly, all the agents are shown to achieve the optimal consensus regardless of the FDI attacks and nonlinear uncertainties.
Engineering Cell Polarization Improves Protein Production in Saccharomyces cerevisiae

Saccharomyces cerevisiae has been widely used as a microbial cell factory to produce recombinant proteins. Therefore, enhancing the protein production efficiency of yeast cell factories to expand the market demand for protein products is necessary. Recombinant proteins are often retained in the secretory pathway because of the limited protein transport performed by vesicle trafficking. Cell polarization describes the asymmetric organization of the plasma membrane cytoskeleton and organelles and tightly regulates vesicle trafficking for protein transport. Engineering vesicle trafficking has broadly been studied by the overexpression or deletion of key genes involved but not by modifying cell polarization. Here, we used α-amylase as a reporter protein, and its secretion and surface-display were first improved by promoter optimization. To study the effect of engineering cell polarization on protein production, fourteen genes related to cell polarization were overexpressed. BUD1, CDC42, AXL1, and BUD10 overexpression increased the activity of surface-displayed α-amylase, and BUD1, BUD3, BUD4, BUD7, and BUD10 overexpression enhanced secreted α-amylase activity. Furthermore, BUD1 overexpression increased the surface-displayed and secreted α-amylase expression by 56% and 49%, respectively. We also observed that the combinatorial modification and regulation of gene expression improved α-amylase production in a dose-dependent manner. BUD1 and CDC42 co-overexpression increased the α-amylase surface display by 100%, and two genomic copies of BUD1 improved α-amylase secretion by 92%. Furthermore, these modifications were used to improve the surface display and secretion of the recombinant β-glucosidase protein. Our study affords a novel insight for improving the surface display and secretion of recombinant proteins.
A Detailed Analysis & Parametric Comparison Of Eeg Processing Models

Electroencephalograms (EEGs) are capable of representing brain signals in terms of numerical vector sets. These signals are used to estimate a wide variety of neurological disorders including Dementias, Epilepsy, Parkinson, Stroke, Transient Ischemic Attack, etc. A wide variety of machine learning based methods are proposed for processing these signals, and each of these are variant in terms of the qualitative nuances, function advantages, application-specific characteristics, qualitative limitations, and deployment-specific future scopes. Thus, it is difficult for researchers to identify optimal EEG processing models for their clinical use cases. These models vary in terms of their performance metrics, which further complicates the process of model selection for clinical use cases. To overcome these issues, this paper initially provides a detailed discussion about existing EEG processing techniques, in terms of their functional details. This will allow readers to identify optimal machine learning techniques, which are suited for the functional use cases. Continuing this discussion, a comparative analysis of these models is done on the basis of their clinical accuracy, precision, computational complexity, delay and scalability metrics, which will assist readers to identify models for their performance-specific use cases. Thus, this text will allow readers to identify optimally performing models for different EEG processing scenarios.
Computational investigation of static multipole polarizabilities and sum rules for ground-state hydrogenlike ions

High-precision multipole polarizabilities, alpha(l) for l <= 4 of the 1s ground state of the hydrogen isoelectronic series, are obtained from the Dirac equation using the B-spline method with Notre Dame boundary conditions. Compact analytic expressions for the polarizabilities as a function of Z with a relative accuracy of 10(-6) up to Z = 100 are determined by fitting to the calculated polarizabilities. The oscillator strengths satisfy the sum rules Sigma(i) f(gi)((l)) = 0 for all multipoles from l = 1 to l = 4. The dispersion coefficients for the long-range H-H and H-He+ interactions are given.
Optical spectroscopy of DPVs and the case of LP Ara

Abstract We present preliminary results of our spectroscopic campaign of a group of intermediate mass interacting binaries dubbed “Double Periodic Variables” (DPVs), characterized by orbital light curves and additional long photometric cycles recurring roughly after 33 orbital periods (Mennickent et al. 2003, 2005). They have been interpreted as interacting, semi-detached binaries showing cycles of mass loss into the interstellar medium (Mennickent et al. 2008, Mennickent & Kołaczkowski 2009). High resolution Balmer and helium line profiles of DPVs can be interpreted in terms of mass flows in these systems. A system solution is given for LP Ara, based on modeling of the ASAS V-band orbital light curve and the radial velocity of the donor star.
On the abundance of gravitational arcs produced by submillimeter galaxies at radio and submm wavelengths

We predict the abundance of giant gravitational arcs produced by submillimeter galaxies (SMGs) lensed by foreground galaxy clusters, both at radio and submm wavelengths. The galaxy cluster population is modeled in a realistic way with the use of semi-analytic merger trees, while the density profiles of individual deflectors take into account ellipticity and substructures. The adopted typical size of the radio and submm emitting regions of SMGs is based on current radio/CO observations and the FIR-radio correlation. The source redshift distribution has been modeled using three different functions (based on spectroscopic/photometric redshift measurements and a simple evolutionary model) to quantify the effect of a high redshift tail on the number of arcs. The source number counts are compatible with currently available observations, and were suitably distorted to take into account the lensing magnification bias. We present tables and plots for the numbers of radio and submm arcs produced by SMGs as a function of surface brightness, useful for the planning of future surveys aimed at arc statistics studies. They show that e.g., the detection of several hundred submm arcs on the whole sky with a signal-to-noise ratio of at least 5 requires a sensitivity of 1 mJy arcsec −2 at 850 μm. Approximately the same number of radio arcs should be detected with the same signal-to-noise ratio with a surface brightness threshold of 20 μJy arcsec −2 at 1.4 GHz. Comparisons of these results with previous work found in the literature are also discussed.
A Unifying Approach to Quaternion Adaptive Filtering: Addressing the Gradient and Convergence

A novel framework for a unifying treatment of quaternion valued adaptive filtering algorithms is introduced. This is achieved based on a rigorous account of quaternion differentiability, the proposed I-gradient, and the use of augmented quaternion statistics to account for real world data with noncircular probability distributions. We first provide an elegant solution for the calculation of the gradient of real functions of quaternion variables (typical cost function), an issue that has so far prevented systematic development of quaternion adaptive filters. This makes it possible to unify the class of existing and proposed quaternion least mean square (QLMS) algorithms, and to illuminate their structural similarity. Next, in order to cater for both circular and noncircular data, the class of widely linear QLMS (WL-QLMS) algorithms is introduced and the subsequent convergence analysis unifies the treatment of strictly linear and widely linear filters, for both proper and improper sources. It is also shown that the proposed class of HR gradients allows us to resolve the uncertainty owing to the noncommutativity of quaternion products, while the involution gradient (I-gradient) provides generic extensions of the corresponding real- and complex-valued adaptive algorithms, at a reduced computational cost. Simulations in both the strictly linear and widely linear setting support the approach.
The "Double-Edged Sword" Effect of Employees' Perceived Supervisor Trust on Work-Family Balance

This paper examines the "double-edged sword" effect of perceived superior trust on employees' work-family balance based on the work-family resource model. Perceived superior trust explains the dual mediating effect of positive emotions and emotional exhaustion by promoting individual resource generation and depletion mechanisms. The results of the empirical analysis based on 284 employees' questionnaire data revealed that: perceived superior trust positively influences employees' work-family promotion and negatively influences employees' work-family conflict through the partial mediation of positive emotion; perceived superior trust positively influences employees' work-family conflict through the full mediation of emotional exhaustion.
Overview of Centers and Institutes for Human-Animal Interaction in the United States

Academic centers and institutes represent critical hubs for the advancement of areas of scholarly and societal interest. We conducted a survey of 16 academic centers and institutes for human-animal interaction (HAI) in the United States to systematically document the current state of academic interest and investment in the field. Areas of focus included demographics, research, engagement, and education. Results indicated a substantial growth of new centers since 1977, particularly over the past decade. Research topics focused primarily on companion animals (largely dogs, cats, and horses) and adults. Engagement efforts centered around online outreach and in-person programming, with 75% of centers providing animal-assisted intervention services. Education opportunities included degrees at the undergraduate (13%), Masters (50%), and Doctoral (25%) level with courses offered in 63% of centers. The growth and productivity of academic centers and institutes for HAI provides evidence for the growing academic influence of the burgeoning field of HAI. The infrastructure these centers provide will be essential in supporting larger-scale research projects, promoting interdisciplinary and community-based research, and educating future leaders of the field.