Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in Alcohol-Related Behaviors and Quality of Life During the COVID-19 Pandemic: Impact of Alcohol Use Disorder Diagnosis and Treatment History.

Multilevel models adjust ed for age, sex, cohort, and enrollment phase. Regression coefficients unstandardized. The ranges of possible scores were from 0 to 40 for the Alcohol Use Disorders Identification Test , 0 to 30 for Penn Alcohol Craving Scale , and 0 to 100 for each of the four World Health Organization QoL - BREF domains.
The stellar metallicity distribution in intermediate-latitude fields with BATC and SDSS data

Based on Beijing–Arizona–Taiwan–Connecticut (BATC) and Sloan Digital Sky Survey (SDSS) photometric data, we adopt the spectral energy distribution (SED) fitting method to evaluate the metallicity distribution for ∼40 000 main-sequence stars in the Galaxy. According to the derived photometric metallicities of these sample stars, we find that the metallicity distribution shifts from metal-rich to metal-poor with the increase of distance from the Galactic Centre. The mean metallicity is about −1.5 ± 0.2 dex in the outer halo and −1.3 ± 0.1 dex in the inner halo and smoothly decreases from −0.4 to −0.8 in the interval 0 5 kpc), so there is little or no metallicity gradient in the halo.
Operational Excellence for Innovative and Purposeful Business for Student Study Of Independent Project at Pt Paragon Technology And Innovation to Create Business Plan Baby Skincare

This study aims to determine operational excellence for innovative and purposeful business for students of independent projects at PT Paragon Technology and Innovation. The type of research used is descriptive analysis method with a qualitative approach. The data used in the form of primary data and secondary data. The final project of joining this Independent Project is implemented into an innovative and purposeful business to create amore natural rich cream, a baby skincare business with natural ingredients and innovating by replacing parabens with leuconostoc fermented as a first bio representative first in Indonesia. Human resource management strategy of study of independent project in this Amore Natural Rich Cream business by applying manpower planning. Where manpower planning is a plan for recruiting human resources in this business by taking into account the qualifications and number of workers needed to make this business run and according to plan. Strategic leadership Students from this business plan is to apply pestel analysis by monitoring the business environment before the business is launched which is seen from the Political, Economic, Social, Technological, Environmental, and Legal aspects. In addition to the PESTEL analysis, it also performs a porters five force. Supply chain management is implemented concept of plan, source, make, deliver, store and customer as well as analyzing demand and production planning. The financial aspect of this business plan is by conducting an investment analysis of the results obtained that this business requires an initial investment as the overall working capital for this business where all this investment is borne 100% from PT Paragon Technology and Innovation. From the results and discussions that have been carried out the investment assessment shows that the discounted payback period (DPP) of the investment plan is 2 years 5 months where investors set a maximum payback period of 4 year. The net present value (NPV) of the investment plan has a positive value of Rp3.358. 277.304. The IRR value of the investment plan is 25% greater than the required interest rate of 15The profitability Index (PI) of the investment plan is greater than 1 (PI > 1). From the investment analysis investment business plan baby skincare is profitable if implemented.
Momentum transfer to small particles by passing electron beams

The force exerted on nanoparticles and atomic clusters by fast passing electrons like those employed in transmission electron microscopes are calculated and integrated over time to yield the momentum transferred from the electrons to the particles. Numerical results are offered for metallic and dielectric particles of different sizes ($0\char21{}500\phantom{\rule{0.3em}{0ex}}\mathrm{nm}$ in diameter) as well as for carbon nanoclusters. Results for both linear and angular momentum transfers are presented. For the electron beam currents commonly employed in electron microscopes, the time-averaged forces are shown to be comparable in magnitude to laser-induced forces in optical tweezers. This opens up the possibility to study optically trapped particles inside transmission electron microscopes.
Helicoidal minimal surfaces of prescribed genus, II

For every genus $g$, we prove that $S^2 \times R$ contains complete, properly embedded, genus-$g$ minimal surfaces whose two ends are asymptotic to helicoids of any prescribed pitch. We also show that as the radius of the $S^2$ tends to infinity, these examples converge smoothly to complete, properly embedded minimal surfaces in $R^3$ that are helicoidal at infinity. We prove that helicoidal surfaces in $R^3$ of every prescribed genus occur as such limits of examples in $S^2\times R$.
A single-spin precessing gravitational wave in closed form

In coming years, gravitational wave detectors should find black hole-neutron star binaries, potentially coincident with astronomical phenomena like short GRBs. These binaries are expected to precess. Gravitational wave science requires a tractable model for precessing binaries, to disentangle precession physics from other phenomena like modified strong field gravity, tidal deformability, or Hubble flow; and to measure compact object masses, spins, and alignments. Moreover, current searches for gravitational waves from compact binaries use templates where the binary does not precess and are ill-suited for detection of generic precessing sources. In this paper we provide a closed-form representation of the single-spin precessing waveform in the frequency domain by reorganizing the signal as a sum over harmonics, each of which resembles a nonprecessing waveform. This form enables simple analytic calculations (e.g., a Fisher matrix) with easily-interpreted results. We have verified that for generic BH-NS binaries, our model agress with the time-domain waveform to 2\%. Straightforward extensions of the derivations outlined here [and provided in full online] allow higher accuracy and error estimates.
SETTING THE STAGE FOR CIRCUMSTELLAR INTERACTION IN CORE-COLLAPSE SUPERNOVAE. II. WAVE-DRIVEN MASS LOSS IN SUPERNOVA PROGENITORS

Supernovae (SNe) powered by interaction with circumstellar material provide evidence for intense stellar mass loss during the final years before core collapse. We have argued that during and after core neon burning, internal gravity waves excited by core convection can tap into the core fusion power and transport a super-Eddington energy flux out to the stellar envelope, potentially unbinding ∼1 solar mass of material. In this work, we explore the internal conditions of SN progenitors using the MESA one-dimensional stellar evolution code in search of those most susceptible to wave-driven mass loss. We focus on simple, order of magnitude considerations applicable to a wide range of progenitors. Wave-driven mass loss during core neon and oxygen fusion happens preferentially in either lower mass (∼20 solar mass zero-age main sequence) stars or massive, sub-solar metallicity stars. Roughly 20% of the SN progenitors we survey can excite 1046–48 erg of energy in waves that can potentially drive mass loss within a few months to a decade of core collapse. This energy can generate circumstellar environments with 10−3–1 solar masses reaching 100 AU before explosion. We predict a correlation between the energy associated with pre-SN mass ejection and the time to core collapse, with the most intense mass loss preferentially occurring closer to core collapse. During silicon burning, wave energy may inflate 10−3–1 solar masses of the envelope to 10–100 s of solar radii. This suggests that some nominally compact SN progenitors (Type Ibc progenitors) will have a significantly different SN shock breakout signature than traditionally assumed.
Dirichlet polynomials, majorization, and trumping

Majorization and trumping are two partial orders which have proved useful in quantum information theory. We show some relations between these two partial orders and generalized Dirichlet polynomials, Mellin transforms, and completely monotone functions. These relations are used to prove a succinct generalization of Turgut’s characterization of trumping.
Searching for Compton-thick active galactic nuclei at z∼ 0.1

Using a suite of X-ray, mid-infrared (mid-IR) and optical active galactic nuclei (AGN) luminosity indicators, we search for Compton-thick AGNs with intrinsic LX > 10 42 erg s −1 at z ∼ 0.03–0.2, a region of parameter space which is currently poorly constrained by deep narrow-field and high-energy (E > 10 keV) all-sky X-ray surveys. We have used the widest XMM–Newton survey (the serendipitous source catalogue) to select a representative subsample (14; ≈10 per cent) of the 147 X-ray undetected candidate Compton-thick AGNs in the Sloan Digital Sky Survey (SDSS) with f X/f [O III] 43 per cent) of our sample appears to be obscured by Compton-thick material with NH > 1.5 × 10 24 cm −2 . Under the reasonable assumption that our 14 AGNs are representative of the overall X-ray undetected AGN population in the SDSS–XMM parent sample, we find that >20 per cent of the optical type-2 AGN population are likely to be obscured by Compton-thick material. This implies a space density of log(� ) > −4. 9M pc −3 for Comptonthick AGNs with LX > 10 42 erg s −1 at z ∼ 0.1, which we suggest may be consistent with that predicted by X-ray background synthesis models. Furthermore, using the 6-µm continuum luminosity to infer the intrinsic AGN luminosity and the stellar velocity dispersion to estimate MBH, we find that the most conservatively identified Compton-thick AGNs in this sample may harbour some of the most rapidly growing black holes (median MBH ≈ 3 × 10 7 M� )i n the nearby Universe, with a median Eddington ratio of η ≈ 0.2.
PARTICLE ACCELERATION AND PLASMA DYNAMICS DURING MAGNETIC RECONNECTION IN THE MAGNETICALLY DOMINATED REGIME

Magnetic reconnection is thought to be the driver for many explosive phenomena in the universe. The energy release and particle acceleration during reconnection have been proposed as a mechanism for producing high-energy emissions and cosmic rays. We carry out two- and three-dimensional (3D) kinetic simulations to investigate relativistic magnetic reconnection and the associated particle acceleration. The simulations focus on electron–positron plasmas starting with a magnetically dominated, force-free current sheet ( &sgr; ≡ B 2 / ( 4 &pgr; n e m e c 2 ) ≫ 1 ? > ). For this limit, we demonstrate that relativistic reconnection is highly efficient at accelerating particles through a first-order Fermi process accomplished by the curvature drift of particles along the electric field induced by the relativistic flows. This mechanism gives rise to the formation of hard power-law spectra f ∝ ( γ − 1 ) − p ? > and approaches p = 1 for sufficiently large σ and system size. Eventually most of the available magnetic free energy is converted into nonthermal particle kinetic energy. An analytic model is presented to explain the key results and predict a general condition for the formation of power-law distributions. The development of reconnection in these regimes leads to relativistic inflow and outflow speeds and enhanced reconnection rates relative to nonrelativistic regimes. In the 3D simulation, the interplay between secondary kink and tearing instabilities leads to strong magnetic turbulence, but does not significantly change the energy conversion, reconnection rate, or particle acceleration. This study suggests that relativistic reconnection sites are strong sources of nonthermal particles, which may have important implications for a variety of high-energy astrophysical problems.
Variational properties of a pumped dynamical system

We earlier constructed a generalized entropy concept to show the direction of time in an evolution following from a Markov generator. In such a dynamical system the entity found changes in a monotonic way starting from any initial state of the system. In this article, we generalize the treatment to the case when population is pumped into the system from levels not explicitly considered. These populations then pass through the coupled levels and exit by decay to levels outside the system. We derive the form of the equation of motion and relate it to our earlier treatments. It turns out that the formalism can be generalized to the new situation. Its physically relevant features are demonstrated and the behavior obtained is illustrated by a numerical treatment of the standard two-level system with pumping and relaxation included.
Multi-Representation Dynamic Adaptation Network for Remote Sensing Scene Classification

In recent years, convolutional neural networks (CNNs) have made significant progress in remote sensing scene classification (RSSC) tasks. Because obtaining a large number of labeled images is time-consuming and expensive and the generalization ability of supervised models is limited, domain adaptation is widely introduced into RSSC. However, existing adaptation approaches mainly aim to align the distribution of features in a single representation space, which results in losing information and limiting the spatial range for extracting domain-invariant features. In addition, some of the methods simultaneously align pixel-level (local) and image-level (global) features for better results but suffer from searching for the best weight of the two parts manually, which is time-consuming and computing-expensive. To overcome the above issues, a novel feature fusion-and-alignment approach named multi-representation dynamic adaptation network (MRDAN) is proposed for cross-domain RSSC. Concretely, a feature-fusion adaptation (FFA) module is embedded into the network, which maps samples to multiple representations and fuses them to obtain a broader domain-invariant feature space. Based on this hybrid space, we introduce a cross-domain dynamic feature-alignment mechanism (DFAM) to quantitatively evaluate and adjust the relative importance of the local and global adaptation losses during domain adaptation. The experimental results on the 12 transfer tasks between the UC Merced Land-Use, WHU-RS19, AID, and RSSCN7 datasets demonstrate the effectiveness of the proposed MRDAN over the state-of-the-art domain adaptation methods in RSSC.
Grothendieck's Homotopy Hypothesis

We construct a "diagonal" cofibrantly generated model structre on the category of simplicial objects in the category of topological categories sCat_{Top}, which is the category of diagrams [\Delta^{op}, Cat_{Top}]. Moreover, we prove that the diagonal model structures is left proper and cellular. We also prove that the category of \infty-groupoids (the full subcategory of topological categories) has a cofibrantly generated model structure and is Quillen equivalent to the model category of simplicial sets, which proves the Grothendieck's homotopy hypothesis.
Quasiprojective Three-Manifold Groups and Complexification of Three-Manifolds

We characterize the quasiprojective groups that appear as fundamental groups of compact $3$-manifolds (with or without boundary). We also characterize all closed $3$-manifolds that admit good complexifications. These answer questions of Friedl--Suciu, \cite{fs}, and Totaro \cite{tot}
AdaptIDS: Adaptive Intrusion Detection for Mission-Critical Aerospace Vehicles

Aerospace and defense industries are particularly vulnerable to cyber threats given their sensitive nature, significantly extending the consequences of security breaches to the national level. Aerospace vehicles are augmented by cooperative control, intelligent, connected, and autonomous systems. The risk against such systems is further amplified due to commonly relying on the MIL-STD-1553 communication bus developed with a high focus on reliability and fault tolerance, albeit with security as a second priority. MIL-STD-1553 (a.k.a., STANAG 3838 by NATO) is a standard that describes a serial data communication bus primarily used in aerospace vehicles for military and civilian applications, including avionics, aircraft, and spacecraft data handling. In the absence of core security measures such as authentication, authorization, and encryption, the bus connecting sensitive functions, including autopilot, GPS, fuel valve switches, and other avionics equipment, is easily vulnerable to a wide range of attacks. This paper proposes, AdaptIDS, a novel adaptive intrusion detection system as a security analytics framework for the MIL-STD-1553 communication bus. AdaptIDS mainly adopts data science principles and leverages advanced deep learning techniques (i.e., the stacking ensemble) to boost its generalization capabilities for detecting unseen patterns of attacks in the dynamic changing environment of aerospace vehicles. Extensive experiments are conducted using two datasets generated from an open-source simulation system, reflecting dynamic real-life scenarios. The evaluation results demonstrate that our solution outperforms existing solutions with high detection effectiveness of 0.99 F1-measure and computational time efficiency.
Pilot-wave theory and quantum fields

Pilot-wave theories provide possible solutions to the measurement problem. In such theories, quantum systems are not only described by the state vector but also by some additional variables. These additional variables, also called beables, can be particle positions, field configurations, strings, etc. In this paper we focus our attention on pilot-wave theories in which the additional variables are field configurations. The first such theory was proposed by Bohm for the free electromagnetic field. Since Bohm, similar pilot-wave theories have been proposed for other quantum fields. The purpose of this paper is to present an overview and further development of these proposals. We discuss various bosonic quantum field theories such as the Schrödinger field, the free electromagnetic field, scalar quantum electrodynamics and the Abelian Higgs model. In particular, we compare the pilot-wave theories proposed by Bohm and by Valentini for the electromagnetic field, finding that they are equivalent. We further discuss the proposals for fermionic fields by Holland and Valentini. In the case of Holland's model we indicate that further work is required in order to show that the model is capable of reproducing the standard quantum predictions. We also consider a similar model, which does not seem to reproduce the standard quantum predictions. In the case of Valentini's model we point out a problem that seems hard to overcome.
Coaches’ Perspectives of the Continuing Coach Education Program in the Development of Quality Coach Education in Singapore

Continuing professional development is considered essential to the improvement of sport coaching standards through the development of coaches’ knowledge. To support continuing professional development participation and learning for Singapore coaches, the Continuing Coach Education (CCE) program was introduced by Sport Singapore. The present study examined the influence of the Continuing Coach Education program on Level 1 Singapore-based coaches registered under the National Registry of Coaches. Utilizing an explanatory sequential quantitative–qualitative mixed methods approach to enhance understanding of participants’ perceptions, National Registry of Coaches Level 1 coaches completed an online questionnaire (n = 124) and participated in a semistructured interview (n = 7). Results revealed: (a) that intrapersonal knowledge was valued over professional and interpersonal knowledge; (b) that holistic development with an emphasis on character development of athletes was valued; (c) coaches’ key learning needs (i.e., sport psychology, use of technology in coaching, and career planning and development); (d) a preference to experience various learning sources (i.e., collaborative, experientially driven, recognized mediated, and internal unmediated), specific learning sources (i.e., self-directed and guided experiential), and improved coach developer facilitation; and (e) main learning motivations (i.e., meeting requirements and content relevance) and barriers (i.e., time and cost). Possible strategies to promote continuing professional development participation and learning for coaches practicing in similar contexts are discussed.
Dynamic Conditional Imitation Learning for Autonomous Driving

Conditional imitation learning (CIL) trains deep neural networks, in an end-to-end manner, to mimic human driving. This approach has demonstrated suitable vehicle control when following roads, avoiding obstacles, or taking specific turns at intersections to reach a destination. Unfortunately, performance dramatically decreases when deployed to unseen environments and is inconsistent against varying weather conditions. Most importantly, the current CIL fails to avoid static road blockages. In this work, we propose a solution to those deficiencies. First, we fuse the laser scanner with the regular camera streams, at the features level, to overcome the generalization and consistency challenges. Second, we introduce a new efficient Occupancy Grid Mapping (OGM) method along with new algorithms for road blockages avoidance and global route planning. Consequently, our proposed method dynamically detects partial and full road blockages, and guides the controlled vehicle to another route to reach the destination. Following the original CIL work, we demonstrated the effectiveness of our proposal on CARLA simulator urban driving benchmark. Our experiments showed that our model improved consistency against weather conditions by four times and autonomous driving success rate generalization by 52%. Furthermore, our global route planner improved the driving success rate by 37%. Our proposed road blockages avoidance algorithm improved the driving success rate by 27%. Finally, the average kilometers traveled before a collision with a static object increased by 1.5 times. The main source code can be reached at this web page: https://heshameraqi.github. io/dynamic_cil_autonomous_driving.
A 48 Gb/s PAM-4 Receiver With Pre-Cursor Adjustable Baud-Rate Phase Detector in 40 nm CMOS

This article presents a 48-Gb/s four-level pulse amplitude modulation (PAM-4) receiver with a Baud-rate clock and data recovery (CDR) suitable for multi-level signaling. By deriving the relation between the vertical eye margin (VEM) and the ratio of main-cursor to pre-cursor, the proposed Baud-rate phase detector (BRPD) adjusts the pre-cursor and finds the lock point with targeted vertical eye opening. Thus, the BRPD offers a unique lock point when used with an adaptive decision feedback equalizer (DFE) where post-cursor $h_{1}$ is removed. Otherwise, the lock point could drift with the conventional Mueller–Müller phase detector (PD). Furthermore, a summer loading of the DFE reduces the input loading of the DFE by embracing the RZ sampler output instead of the conventional NRZ output, which adds to the delay associated with an RS latch. A prototype chip fabricated in 40-nm CMOS technology consists of an analog front-end (AFE), a phase rotator (PR), a current digital-to-analog converter (DAC), and synthesizable digital logic (SDL), occupying a total active area of 0.24 mm2. The proposed PAM-4 receiver achieves a bit-error rate (BER) of less than 10−11 at 48 Gb/s and offers an energy efficiency of 2.42 pJ/b.