Miracle-dz/UniFAR-FTUs huggingface dataset:
Numerical Study on Aging Dynamics in the 3D Ising Spin-Glass Model. II. Quasi-Equilibrium Regime of Spin Auto-Correlation Function

Using Monte Carlo simulations, we have studied isothermal aging of three-dimensional Ising spin-glass model focusing on quasi-equilibrium behavior of the spin auto-correlation function. Weak violation of the time translational invariance in the quasi-equilibrium regime is analyzed in terms of effective stiffness for droplet excitations in the presence of domain walls. Within the range of computational time window, we have confirmed that the effective stiffness follows the expected scaling behavior with respect to the characteristic length scales associated with droplet excitations and domain walls, whose growth law has been extracted from our simulated data. Implication of the results are discussed in relation to experimental works on ac susceptibilities.
Interpretable Traffic Event Analysis with Bayesian Networks

Although existing machine learning-based methods for traffic accident analysis can provide good quality results to downstream tasks, they lack interpretability which is crucial for this critical problem. This paper proposes an interpretable framework based on Bayesian Networks for traffic accident prediction. To enable the ease of interpretability, we design a dataset construction pipeline to feed the traffic data into the framework while retaining the essential traffic data information. With a concrete case study, our framework can derive a Bayesian Network from a dataset based on the causal relationships between weather and traffic events across the United States. Consequently, our framework enables the prediction of traffic accidents with competitive accuracy while examining how the probability of these events changes under different conditions, thus illustrating transparent relationships between traffic and weather events. Additionally, the visualization of the network simplifies the analysis of relationships between different variables, revealing the primary causes of traffic accidents and ultimately providing a valuable reference for reducing traffic accidents.
More on ghosts in DGP model

It is shown by an explicit calculation that the excitations about the self-accelerating cosmological solution of the Dvali–Gabadaze–Porrati model contain a ghost mode. This raises serious doubts about viability of this solution. Our analysis reveals the similarity between the quadratic theory for the perturbations around the self-accelerating Universe and an Abelian gauge model with two St¨uckelberg ﬁelds.
Experimental study of a turbulent pipe flow through a fractal plate

We study flows forced through plates in a circular wind-tunnel. The plates are based on different iterations of a pattern which would correspond to the generation of a fractal object. Two types of patterns are considered: one leading to an orifice with a fractal perimeter, the other to a fractal equivalent of a perforated plate. We propose this approach as a systematic way to introduce scales forcing and construct a scale by scale multiscale flow. For the sake of comparison we also consider simple orifice plates having a different number of sharp edges but which are based on a single scale geometry (monoscale orifices). In terms of analysis we focus on the pressure drop across the plate as in terms of engineering application this is the most salient effect of the plate multiscale generation. We measure the pressure recovery as a function of the distance from the plate. We also use hotwire anemometry to understand the action of the fractal-based plate on the flow and measure velocity statistics on the pipe's axis. We found that as far as pressure drop recovery is concerned, it is not always necessary to choose large numbers of iteration for the fractal pattern. However, the velicity statistics can remember the order of the fractal generation over a long distance. In certain cases it would require a very long pipe to quantify the full recovery from the fractal-generated turbulent flow.
Bounding zeta on the 1-line under the partial Riemann hypothesis

We provide explicit bounds in the theory of the Riemann zeta-function at the line $\Re{s}=1$, assuming that the Riemann hypothesis holds until the height $T$. In particular, we improve some bounds, in finite regions, for the logarithmic derivative and the reciprocal of the Riemann zeta-function.
Pulsatile Chronotherapeutic Drug Delivery for Controlling Early Morning Surge in Blood Pressure; Effect of Coating on Eplerenone In-vitro , In- vivo Release and Urinary Na/K Ratio

The objective of the present study was to develop time delayed chronotherapeutic formulation of Eplerenone (Ep) to provide rapid drug release after a pre-determined lag time for the treatment of early morning hypertension. Cyclodextrin complexation was used to prepare fast release Ep core tablets. The developed core tablets were then coated with different rate-controlling polymers using compression coating technique. The developed tablets were evaluated for hardness, friability, drug content and swelling index. The in-vitro drug release was carried out to study the effect of different coating materials on drug release and lag time. Tablets selected for stability study were those showing lag time of 5–7 hours followed by complete drug release; F2, F3, F7, F8, and F12. The in-vivo study was carried out on tablets with the highest t 90 as compared to commercial tablets after being administered to healthy human volunteers where plasma Ep and urinary Na/K ratio were determined. Results suggested that this approach was able to provide delayed release Ep formulations that will be useful for patients with morning surge in blood pressure.
Learning to Cut with Reinforcement Learning

—Integer programming is a computationally difﬁcult problem in which a objective function must be minimized inside a feasible region with the optimization variables required to take on integral values. Amidst various heuristics available for solving this problem, a popular class of algorithms are ’cutting-plane’ methods, which iteratively restrict the feasible region using information from solving a sequence of linear programs instead. At each iteration, these algorithm pick an additional constraint which further restricts the feasible region. Such choices are Markovian given the current set of constraint and available options to restrict or ”cut” the region, and hence lend themselves to formulation as a Markov Decision Process. In this project, I replicate results that build on this MDP assumption and formulate the choice of which region to cut as a reinforcement learning problem, combining the strength of SOTA linear program solvers and the approximation power of supervised learning. I explore some powerful RL techniques we have studied in class as an alternative to evolutionary strategy training, and report results on two policy gradient techniques. Noticing that calls to simplex solvers are the main time-sink in training, I further reﬂect on how we can use pre-training or alternate formulations of the problem to improve the sample efﬁciency of the learning task.
Increasing Deterrence and Efficiency Through

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Nuclear fusion enhances cancer cell killing efficacy in a protontherapy model

Protontherapy is hadrontherapy fastest-growing modality and a pillar in the battle against cancer. Hadrontherapy superiority lies in its inverted depth-dose profile, hence tumour-confined irradiation. Protons, however, lack distinct radiobiological advantages over photons or electrons. Higher LET (Linear Energy Transfer) $^{12}$C ions can overcome cancer radioresistance: DNA lesion complexity increases with LET, resulting in efficient cell killing, i.e. higher Relative Biological Effectiveness (RBE). However, economic and radiobiological issues hamper $^{12}$C-ion clinical amenability. Thus, enhancing proton RBE is desirable. To this end, we exploited the p + $^{11}$B $\rightarrow$3$\alpha$ reaction to generate high-LET alpha particles with a clinical proton beam. To maximize the reaction rate, we used sodium borocaptate (BSH) with natural boron content. Boron-Neutron Capture Therapy (BNCT) uses $^{10}$B-enriched BSH for neutron irradiation-triggered alpha-particles. We recorded significantly increased cellular lethality and chromosome aberration complexity. A strategy combining protontherapy ballistic precision with the higher RBE promised by BNCT and $^{12}$C-ion therapy is thus demonstrated.
Advancing the Understanding and Measurement of Workplace Stress in Remote Information Workers from Passive Sensors and Behavioral Data

Workplace stress has been increasing in recent decades and has worsened by the unique demands imposed by COVID-19 and the new remote/hybrid work settings. High-stress working conditions can be detrimental to the health and wellness of workers and can lead to significant business costs in terms of productivity loss and medical expenses. An essential step toward managing stress involves finding comfortable ways to sense workers and recognizing stress as soon as it happens. This work explores the potential value of using pervasive sensors such as keyboards, webcams, and behavioral data such as calendar and e-mail activity to passively assess individual stress levels of work in real-life. In particular, we collected a large corpus of such data from 46 remote information workers over one month and asked them to self-report their stress levels and other relevant factors several times a day. Analysis of the data demonstrates that passive sensors can effectively detect both triggers and manifestations of workplace stress and that having access to prior data of the worker is critical for developing well-performing stress recognition models. Furthermore, we provide qualitative feedback capturing workers' preferences in workplace stress monitoring.
Variable Stars in Leo A: RR Lyrae Stars, Short-Period Cepheids, and Implications for Stellar Content

We present the results of a search for short-period variable stars in Leo A. We have found 92 candidate variables, including eight candidate RR Lyrae stars. From the RR Lyrae stars, we measure a distance modulus of (m-M)0 = 24.51 ± 0.12, or 0.80 ± 0.04 Mpc. This discovery of RR Lyrae stars confirms for the first time the presence of an ancient (older than ∼11 Gyr) population in Leo A, accounting for at least 0.1% of the galaxy's V luminosity. We have also discovered a halo of old (more than ∼2 Gyr) stars surrounding Leo A, with a scale length roughly 50% larger than that of the dominant young population. We also report the discovery of a large population of Cepheids in Leo A. The median absolute magnitude of our Cepheid sample is MV = -1.1, fainter than 96% of SMC and 99% of LMC Cepheids. Their periods are also unusual, with three Cepheids that are deduced to be pulsating in the fundamental mode having periods of under 1 day. Upon examination, these characteristics of the Leo A Cepheid population appear to be a natural extension of the classical Cepheid period-luminosity relations to low metallicity, rather than being indicative of a large population of "anomalous" Cepheids. We demonstrate that the periods and luminosities are consistent with the expected values of low-metallicity blue helium-burning stars (BHeB's), which populate the instability strip at lower luminosities than do higher metallicity BHeB's.
Solution Structure of the Mycobacterium tuberculosis EsxG (cid:1) EsxH Complex FUNCTIONAL IMPLICATIONS AND COMPARISONS WITH OTHER M. TUBERCULOSIS Esx FAMILY COMPLEXES *

Mycobacterium tuberculosis encodes five type VII secretion systems that are responsible for exporting a number of proteins, including members of the Esx family, which have been linked to tuberculosis pathogenesis and survival within host cells. The gene cluster encoding ESX-3 is regulated by the availability of iron and zinc, and secreted protein products such as the EsxG (cid:1) EsxH complex have been associated with metal ion acquisition. EsxG and EsxH have previously been shown to form a stable 1:1 heterodimeric complex, and here we report the solution structure of the complex, which features a core four-helix bundle decorated at both ends by long, highly flexible, N- and C-terminal arms that contain a number of highly conserved residues. Despite clear similarities in the overall backbone fold to the EsxA (cid:1) EsxB complex, the structure reveals some striking differences in surface features, including a potential protein interaction site on the surface of the EsxG (cid:1) EsxH complex. EsxG (cid:1) EsxH was also found to contain a specific Zn 2 (cid:1) binding site formed from a cluster of histidine residues on EsxH, which are conserved across obligate mycobacterial pathogens including M. tuberculosis and Mycobacterium leprae . This site may reflect an essential role in zinc
Arbitrarily Parallelizable Code: A Model of Computation Evaluated on a Message-Passing Many-Core System

The number of processing elements per solution is growing. From embedded devices now employing (often heterogeneous) multi-core processors, across many-core scientific computing platforms, to distributed systems comprising thousands of interconnected processors, parallel programming of one form or another is now the norm. Understanding how to efficiently parallelize code, however, is still an open problem, and the difficulties are exacerbated across heterogeneous processing, and especially at run time, when it is sometimes desirable to change the parallelization strategy to meet non-functional requirements (e.g., load balancing and power consumption). In this article, we investigate the use of a programming model based on series-parallel partial orders: computations are expressed as directed graphs that expose parallelization opportunities and necessary sequencing by construction. This programming model is suitable as an intermediate representation for higher-level languages. We then describe a model of computation for such a programming model that maps such graphs into a stack-based structure more amenable to hardware processing. We describe the formal small-step semantics for this model of computation and use this formal description to show that the model can be arbitrarily parallelized, at compile and runtime, with correct execution guaranteed by design. We empirically support this claim and evaluate parallelization benefits using a prototype open-source compiler, targeting a message-passing many-core simulation. We empirically verify the correctness of arbitrary parallelization, supporting the validity of our formal semantics, analyze the distribution of operations within cores to understand the implementation impact of the paradigm, and assess execution time improvements when five micro-benchmarks are automatically and randomly parallelized across 2 × 2 and 4 × 4 multi-core configurations, resulting in execution time decrease by up to 95% in the best case.
Artificial Intelligence Based Study Association between p53 Gene Polymorphism and Endometriosis: A Systematic Review and Meta-analysis

Background The P53 gene is critical to the onset and progression of cancers. Currently, relevant study findings indicate that the p53 gene may have a strong association with the risk of endometriosis, but these findings have not been united. To gather more statistically meaningful clinical data, we used meta-analysis to examine the relationship between the rs1042522 single nucleotide polymorphism of the tumor suppressor gene p53 and the incidence of endometriosis. Methods Through a comprehensive literature survey of PubMed, MEDLINE, EMBASE, Springer, and Web of Science literature databases, we obtained a clinical control case study on the relationship between p53 gene polymorphism and the prevalence of female endometriosis and finally traced the relevant references included. The quality of the literature included in this study was evaluated, and Revman5.3 was used to complete the meta-analysis. Results This research includes eight publications. The total number of cases in the study group was 1551, whereas the total number of cases in the control group was 1440. The findings of the sensitivity analyses of each omitted piece of the literature revealed no significant difference. The results of the meta-analysis showed that there were significant differences in the GG gene frequency (OR = 0.56, 95%CI (0.38, 0.92), P = 0.003), allele G (OR = 2.46, 95%CI (1.41,4.29), P = 0.002), and allele C (OR = 0.62, 95%CI (0.46, 0.84), P = 0.002) between the study group and the control group (P < 0.01), but there was no significant difference in the GC gene frequency (OR = 1.17, 95%CI (1.01,1.36), P = 0.03), and the CC gene frequency (OR = 1.25, 95%CI (0.85,1.82), P = 0.26) (P > 0.01). Conclusion Our study results show that there is a significant correlation between the single nucleotide of the p53 gene and the incidence rate of female endometriosis, in which the decrease of the GG gene frequency and the increase of allele C are likely to increase the risk of such diseases.
Noncoding RNA in the Regulation of Acute Aortic Dissection: From Profile to Mechanism

Aortic dissection is a life-threatening condition caused by a tear in the intimal layer of the aorta or bleeding within the aortic wall, resulting in the separation of the layers of the aortic wall. As Nienaber reported, aortic dissection is most common in people 65–75 years old and has an incidence of 35 cases per 100,000 people per year in this population. Many pathogenic factors are involved in aortic dissection, including hypertension, dyslipidemia, and abnormality of the aortic intima caused by genetic variation. However, with the development of gene sequencing and transgenic technology, genetic methods are being used for the diagnosis and treatment of diseases, including acute aortic dissection. Genetic research on acute aortic dissection began around 2006. Recently, research on acute aortic dissection has mainly focused on microRNA (miRNA). Studies have found that miRNA plays a critical regulatory role in the occurrence and development of acute aortic dissection. By regulating miRNA expression, acute aortic dissection can be prevented and treated.
Frontloading the Unemployment Bene t: An Empirical Assessment

In November 2005, the Hungarian government frontloaded the unemployment bene t path, while keeping the total bene t amount that could be collected over the unemployment spell constant. We estimate the e ect of this reform on non-employment duration using a regression discontinuity research design, where we exploit the sharp change in the bene t-path for those who claimed bene t after 1st of November 2005. We nd that non-employment duration fell by 1.5 weeks after November 2005, while reemployment wages and the duration of new jobs remained the same. We show that the decrease in non-employment duration was large enough to make the bene t reform revenue neutral. Our welfare evaluation for this reform is positive: frontloading increased job nding, it made some of the unemployed better o , and did not cost anything to the taxpayers. ∗We would like to thank Lajos Bódis, David Card, Stefano DellaVigna, Hedvig Horváth, Andrew Johnston, Gábor Kézdi, Patrick Kline, Mihály Szoboszlai, Emmanuel Saez, Johannes Schmieder, Owen Zidarand the audiences of UC Berkeley, Central European University, the conference at Szirák, 4th Seek conference at Mannheim. We are grateful for János Köll®, Kitti Varadovics, Mónika Bálint, Dániel Biró for giving us access to the administrative data and providing continuous help throughout the project and to Csaba Nagy and Zsolt Pelek for explaining the practical implementation of the reform. We gratefully acknowledge the support of Firms, Strategy and Performance Lendület Grant of the Hungarian Academy of Sciences . § a.lindner@ucl.ac. uk, §§reizer_balazs@phd.ceu. edu
Boson sampling with Gaussian measurements

We develop an alternative boson sampling model operating on single-photon states followed by linear interferometry and Gaussian measurements. The hardness proof for simulating such continuous-variable measurements is established in two main steps, making use of the symmetry of quantum evolution under time reversal. Namely, we first construct a twofold version of scattershot boson sampling in which, as opposed to the original proposal, both legs of a collection of two-mode squeezed vacuum states undergo parallel linear-optical transformations. This twofold scattershot model yields, as a corollary, an instance of boson sampling from Gaussian states where photon counting is hard to simulate. Then, a time-reversed setup is used to exhibit a boson sampling model in which the simulation of Gaussian measurements -- namely the outcome of eight-port homodyne detection -- is proven to be computationally hard. These results illustrate how the symmetry of quantum evolution under time reversal may serve as a tool for analyzing the computational complexity of novel physically-motivated computational problems.
Sustainability and Gender Perspective in Food Innovation: Foods and Food Processing Coproducts as Source of Macro- and Micro-Nutrients for Woman-Fortified Foods

Micro- and macro-nutrient deficiencies among women are considered a global issue that the food industry has not adequately considered until recently. The industry must provide and guarantee a diversity of food products worldwide that allow women to get a correct and balanced diet according their life stage. The food industry must focus on this challenge within a framework of sustainable production, minimizing the use of natural resources and avoiding the emission of waste and pollutants throughout the life cycle of food. Food coproducts are presented as potential bioactive functional compounds which can be useful for technological purposes, due to the fact that they can serve as non-chemical, natural and health-improving food ingredients. In this review, we focus on the potential use of food processing coproducts which must be part of a strategy to promote and improve women’s health and well-being. This knowledge will make it possible to select potential ingredients from coproducts to be used in the fortification of foods intended for consumption by females and to introduce sustainability and gender perspectives into food innovation. The attainment of fortifications for foods for women has to be linked to the use of sustainable sources from food coproducts in order to be economically viable and competitive.